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s r
ir • • - • / !
. • • . • • : • /
- APRL/95/1
INTERNATIONAL CENTRE FORTHEORETICAL PHYSICS
ATMOSPHERIC PHYSICSAND
RADIOPROPAGATION LABORATORY
INTERNATIONALATOMIC ENERGY
AGENCY
UNITED NATIONSEDUCATIONAL,
SCIENTIFICAND CULTURALORGANIZATION
RADIOWAVE PROPAGATION MEASUREMENTSIN SENEGAL
F. Postogna
I.H. Sarpun
S.M. Radicella
and
K.A. Hughes
MIRAMARE-TRIESTE
ii£,a:;r:::':":::: •
APRL/95/1
International Atomic Energy Agencyand
United Nations Educational Scientific and Cultural Organization
INTERNATIONAL CENTRE FOR THEORETICAL PHYSICS
ATMOSPHERIC PHYSICSAND
RADIOPROPAGATION LABORATORY
RADIOWAVE PROPAGATION MEASUREMENTS IN SENEGAL
F, Postogna, I-H. Sarpun', S.M. RadicelSaAtmospheric Physics and Radiopropagation Laboratory,
International Centre for Theoretical Physics, Trieste, Italy
and
K.A. HughesRadiocommunication Bureau, International Telecommunication Union (ITU),
Geneva, Switzerland.
ABSTRACT
This report describes the results of over two years of radiowave propagation measure-ments undertaken in Senegal under the auspices of the ITU. The signal level of a TVtransmitter located in Ziguinchor was received in Bambey (approximately 140 km eastof Dakar). The frequency band was VHF and the path length, 237 km. Statistical anal-ysis has been made of the field strength behaviour, together with a critical comparisonbetween predicted values, using ITU-R recommended methods, and the actual measureddata. The results show that the measured values of field strength were significantly higherthan predicted, indicating that the occurrence of super-refractivity in the region is greaterthan previously thought. The necessity for predictions to take into account seasonal anddiurnal variations is stressed.
The analysis described in this report represents a collaborative study undertakenwithin the framework of the Memorandum of Understanding (1993), established betweenThe International Telecommunication Union (IT)) and The International Centre for The-oretical Physics (ICTP).
MIRAMARE - TRIESTE
July 1995
'Permanent address: Osmangazi University, Eskisehir, Turkey.
PREFACE
The ICTP-APRL reports consist of preprints relevant toresearch and development work done at the AtmosphericPhysics and Radiopropagation Laboratory of theInternational Centre for Theoretical Physics with theparticipation of visiting scientists.
More information can be obtained by contacting:
Prof. Sandro M. RadicellaAtmospheric Physics and Radiopropagation LaboratoryP.O. Box 58634100 TriesteItalyPhone: +39 40 2240331FAX: +39 40 224604E-mail: rsandro@ictp.trieste.it
1. INTRODUCTION
Planning of radio services needs a good knowledge of the propagation
characteristics of the area of interest. Such information is required, not only to ensure that
an adequate service will be provided, but also to help assess the potential for interference
between stations working in the same band or, in a worse case, stations sharing the same
frequency. To help engineers in the planning of the broadcast services, ITU has developed
propagation prediction methods that usually give a representation of field-strength values
exceeded at 50% of the locations for different percentages of time and path lengths [2,3].
The set of data upon which these propagation prediction methods are based usually
comes from cumulative frequency distributions of field-strength measurements considered
on a yearly basis. In the main, these measurements have been made in temperate regions of
the world. As a consequence, they are not very representative of areas subject to
anomalous propagation effects such as extreme super-refractivity and ducting which are
often prevalent in low latitude tropical areas. The aim of the current experiment, therefore,
was to acquire data from such a tropical region in Africa and, in turn, to obtain
corresponding statistics of field strength. The results indicate that, not only do the current
prediction methods generally under-estimate the field strength for the propagation path
used in this experiment, but also that yearly statistics are too broad, and that seasonal and
diurnal variations must be taken into account for a realistic prediction.
2. EXPERIMENT
2.1. GENERAL
Senegal is located in western Africa, bordering the North Atlantic Ocean between
Guinea-Bissau and Mauritania. The total area is 196,190 km1. Senegal's climate is tropical
i.e. hoi and humid; there are two main seasons: rainy season (approximately April to
October) with strong south-east winds; dry season (approximately November to March)
dominated by hot, dry harmaltan winds. The terrain is generally low rolling plains rising to
foothills in south-east [1].
2.2. VHF PROPAGATION MEASUREMENT EXPERIMENT
The aim of the experiment was to carry out continuous measurements of the field
strength resulting from a TV transmitter in the VHF band over a path length of about 240
km. Table 1 gives details of the experiment.
"•*"•« t ZE j j ^E J5. .
DETAILS OFSENEGAL EXPERIMENT
FrequencyTx ant. height
Rx ant. heightTx e.r.p.
Path distance
215 MHz
200 m
10m
10 kW
237 km
Table I
The installation of the experiment was undertaken in November 1992 by the
Deutsche Bundespost, under the guidance of the BDT and BR of the ITU. Local support
was provided by engineers from RTS (Radiodiffusion Television du Se'ne'gal) and from
SONATEL, and it was this team of engineers who continued to monitor the experiment
and to collect the data throughout the duration of (he experiment. Subsequent detailed
analysis of the data was undertaken by ICTP.
The field-strength equipment was provided by Rohde & Schwarz. The receiver
(ESV) was installed at the SONATEL building at Bambey (located about 140 km east of
Dakar), with the antenna (yagi) placed 10 m above local ground level. The transmitter was
a TV station at Ziguinchor (in the south of Senegal) with a quoted e.r.p. of 10 kW. Figure
I indicates the positions of the transmitter and receiver. Although a detailed terrain profile
has not been acquired, the propagation path can be considered as essentially flat, with no
significant terrain obstacles.
The experiment was initiated in December 1992 and was expected to have a
duration of at least two years. Unfortunately a break-down of the receiver happened in
October 1993 and only after five months the experiment started again. A failure occurred
also between September and November 1994, Table 2 indicates the number of days for
each month that field strength data were obtained.
2.3 DATA PROCESSING
The total database of measurements obtained from the experiment amounted to
some 27 MB. In order to handle a database of such dimensions, purpose-written software
was developed by ICTP for both data reduction and subsequent analysis. The main
analysis program allowed the user to view the measurement data and to calculate
cumulative distributions over selected time periods. Further programs were also produced
for more detailed statistical analyses and comparison purposes, supported by proprietary
software. To produce the results presented in this report, over 700 data files were
necessary.
Figure I
Map of Senegal showing locations
of Tx (Ziguinchor) and Rx {Bambey)
Number of days for which field strength data were obtained
January
February
March
April
May
JuneJuly
August
September
October
November
December
1992
-
-
_
_
-
23
1993
31
28
31
30
31
30
31
16
2
7
-
-
1994
-
7
30
31
22
31
31
6-
9
31
1995
31
28
31
30
23_
_
_
_
-
-
Table 2
Number of days per month for which field strength data were obtained
3. DATA ANALYSIS
3.1. FIELD STRENGTH CALCULATION AND DATA RECORDING
PROGRAMME
The measured signal level received in Bambey was recorded on floppy discs as
values of voltage, and these were subsequently converted to values of field strength for
statistical analysis on a PC. Great care was taken in the conversion process to ensure that
correct values of field strength were calculated.
Using information provided by RTS on the transmitted power from Ziguinchor, the
free-space field strength at Bambey was estimated to be 69.5 dBfiV/m. Taking into
account the possibility of smaJl variations in the transmitted power from time to time, and
also in the characteristics of the receiving equipment, it is estimated that the overall error
in the field strength values is no greater than + 2 dB and that comparisons with
predictions will be accurate to about ±4 dB.
According to RTS, the normal schedule of broadcasts from Ziguinchor was:
Monday to Friday, approximately 1600 to 2400 hours,
weekends and national holidays, approximately 1200 to 2400 hours.
Some variation in this schedule was apparent from time to time.
For analysis purposes, it was necessary to select measurement data only from those
periods corresponding to times of the broadcast transmission. Since the transmission time
varied slightly from day-to-day, a simple means of selecting (he required data was to set a
lower limit to the field strength values below which the data would be ignored in the
statistical analysis. This limit, 7 dBu.V/m, corresponded to a value just above the "noise
floor". Since the signal from the transmitter could be received in Bambey for most of the
time, very few "real" data have been lost from the analysis by using this cut-off value.
3.2 CUMULATIVE DISTRIBUTION FOR THE ENTIRE DATABASE
Figure 2 shows a cumulative frequency distribution for the entire database of
measurements in accordance with the data listed in Table 2. The figure shows the value of
field strength (dB(iV/m) exceeded as a function of the percentage of measurement time.
As stated earlier, the measurement time corresponded.to the evening hours (approximately
1600 - 2400 h) on week-days and to afternoon and evening hours (approximately 1200 -
2400 h) at weekends.
i
10.00
Percentage of time100.00
Figure 2
Cumulative frequency distribution for (he entire database of measurements
It is interesting to compare (he values for 50, 10 and I % of the time with (hose
given by established prediction methods. One well-know method is that of
Recommendation ITU-R PN.37O [2] which contains families of Held strength curves, for
the VHF and UHF bands, as a function of distance for various antenna heights and
percentages of time. Propagation curves are also contained in the Final Acts of the
Regional Administration Conference for the planning of VHF/UHF TV broadcasting for
Africa (GE89) [3]. For the region of west Africa containing Senegal, the appropriate
propagation curves from the two prediction methods are identical and correspond to those
for a warm maritime region. Table 3 shows a comparison between the measured data and
prediclions using (hese two prediction methods. (N.B. The value of the free-space field
strength for the path is estimated as 69.5 dB(lV/m.)
Senegal measurements
(Dec.!992
- May 1995)
Recommendation 1TU-
R PN.37O
(orGE89)
50% lime
25.5
13.0
10% lime
55.5
27.5
I % time
67
44.0
Table 3
Comparison of predicted and measured field strengths (dB|iV/m)
The results indicate that the predicted values are seriously under-estimated. The high
measured values are a clear indication of the frequent occurrence of super-refractive
behaviour in the region of Senegal,
3.3 MONTHLY CUMULATIVE FREQUENCY DISTRIBUTIONS AND
COMPARISONS WITH PREDICTIONS
For a more detailed investigation of the measured signal levels, cumulative
distributions have been derived for each month for which more than fifteen days of data
were obtained. These are shown in Figure 3. Two aspects are immediately apparent.
Firstly, when comparing the values with those predicted for time percentages of 50, 10
and t (using Rec. ITU-R PN.370 [2], or GE89 [3]), it is clear that in many rases the
predictions are seriously underestimated. Moreover, there are many examples where the
value at I % approaches, or even tends to exceed, the free-space value of 69.5 dBfiV/m.
The second observation is that considerable variation is present from one month to
another. Again, comparison with predictions also shows considerable variation, with some
months giving reasonable agreement with prediction (e.g. January 1995) and others, very
poor agreement (e.g. April 1993). This strong monthly, or seasonal, variation is indicative
of the varying degree of super-refractivity from one month to another which, in turn,
reflects the meteorological behaviour prevailing in the region.
Inspection of Figure 3 shows that the highest values tend to occur from about March
to June with the lowest values from about July to September. Whilst this does not
correspond precisely with the well-defined seasons, this result is in broad agreement with
that obtained from a similar experiment in Burkina Faso [4], undertaken from 1986 -
1989, insofar as the highest values were recorded during the rainy season. It is difficult to
be more precise about any such relationship without a detailed study of the prevailing
meteorology, and this is to be the subject of a further study. However, the association
between the high field strength values and the rainy season probably implies a strong
influence of the humidity component of the refractivity - an observation that has been
made elsewhere [41-
It should be noted that prediction methods such as that in Rec. ITU-R PN.370 can
make some allowance for the degree of terrain irregularity along the propagation path of
interest. The basic propagation curves given in these prediction methods are appropriate
for "gently rolling terrain" which would correspond to terrain exhibiting a greater degree
of irregularity than would be present on the path in this study. Corrections can be applied
to the predictions according lo the actual amount of terrain irregularity on the path of
interest and, for the present case, i( is estimated that such a correction would increase the
predicted field strength by some 3 dB, thus reducing the general discrepancy between the
predictions and measurements. Nevertheless, the underestimation in predicted field
strength is still obvious in most cases.
Dec-92
1 10Percentage of time
Fig. 3 (a)
Feb-93
100
1 10Percentage of time
Fig. 3 (c)
100
Jan-93
-——.
-
1Si
807060
.. I . .1
,E so • n+v.3 40g 3 0
20100
... ' i '
11.
- J- L
;'t
. 1
- ---
1 1
8070
'• 60: 1 50j = 40
?3020
^ 10U 0
10 100Percentage of time
Fig. 3 (b)
Mar-93
r T TI
•:.[:i 1 -
"IK
i-j—
i
^--
1 10 100Percentage of time
Fig. 3(d)
Apr-93
10 100Percentage of time
Fig. 3 (e)
Jun-93
1 10 100
Percentage of time
Fig. 3 (g)
Aug-93
1 10 100Percentage of time
May-93
....
|-"
....
^. |
r\\\-
\ s
10
Percentage of time
Fig. 3 (f)
Jul-93
100
0 -10
Percentage of time
Fig. 3 (h)
Apr-94
I
Sjs1
10
Percentage of time100
Fig. 3 (i) Fig- 3 (j)
May-94 Jun-94
1 10 100
Percentage of time
Fig. 3{k)
Jul-94
0.001.00 10.00 100.00
Percentage of time
Fig. 3 (m)
Dec-94
10
Percentage of time
Fig. 3 (o)
8070-60 |5040 "i3020100 -
10 100
Percentage of ttme
Fig. 3 (I)
Aug-94
10 100
Percentage of time
10 100
Percentage of time
Fig. 3(p)
10
- «LJ»'Jtiit.. IB. J
Feb-95 Mar-95
10 100
Percentage of time
Fig. 3(q)
Apr-95
10 100
Percentage of time
Fig. 3 (r)
May-95
m1 10 100
Percentage of time
Fig. 3 (s)
10 100
Percentage of time
Fig. 3 (t)
3.4 MONTHLY VARIATION DURING THE EVENING HOURS
To investigate further the monthly variation of the received field strength,
cumulative distributions on a monthly basis were calculated for the time period between
2000 and 2300 hours. We choose this time window because it corresponds to the hours of
the largest TV audience and therefore to when the impact of interference phenomena
would be the greatest. The following plot in Figure 4 shows the monthly variability of the
field strength at three percentages of time, over a nine month period.
From the figure it is also clear that the field-strength level for 50% of time, predicted
from Rec. ITU-R PN.37O [2] (or from GE89 [3]), is too low and sometimes the difference
between the predicted level and the one obtained from measured values is greater than 30
dBuV/m.
70
«)
Ml
S 40>
§ 10
21)
10
0r
c
k
1 ri
\ i \U-
/ " • " * • " - —
5 s ?'
Months
\
\
Jun-
93
r
i =*
50*oltimc
— — 10%ofomc
" - • - 70*0111™
Figure 4
Monthly varialion of field strength at three time percentages
In addition, we have taken three representalive months in the period from December
1992 and August 1993 (January, April, and July) to underline the strong seasonal varialion
observed during the experiment. The corresponding cumulative distributions are given
below in Figures 5 to 7.
Monthly Cum. Dist., In Jan 93 (2000 to 2300 h)
20.00
10.00
0.00
-----
s
!f
4
...
N
-
s
!
1.00 10.00
Percentage of time
100.00
Figure 5
12
70 00
60.00
SO.OO
| 40.00aM 30.00
20.00
10 00
0.001.<M
Monthly Cum
\ -
J
• • —
. Dist.
I
Parc
-
:e
in Apr 93 (2000 to 2300 h)
1
it
-
0 00
je of time
,
ss\
1C
I])0
.00
Figure 6
70,00
60.00
50.00 •
| 40.00
g 30.00
20.00
10.00
1.
Mont
30
hly Cum. I
i
—
l ist. ,
I
i
n Jul 93 (20DO t o :
1 „
300
•sS\
10.00 100.00
Percentage of time
Figure 7
3.5 HOURLY VARIATION OF FIELD STRENGTH
To investigate the diurnal varialion of the field strength, we have calculated the
cumulative frequency dislribution on a time window of 60 minutes centred on the hour
13
from 1200 to 2300 during every month for which data were available. Then we extracted
the percentage of time at every hour corresponding to ihe following field strength levels -
greater than 10, 20. 30, 40, 50 and 60 dBuV/m.
To highlight the year-to-year variation, we compared the diurnal cumulative
distributions in ihe same month, for different years, Figures 8 to 10 show the results for
the three representative months chosen before.
Compiri ton of Jin-93 and Jan-BS
12 13 14 15 16 17 18 19 20 21 21 23
- 9 3 . >10HBuV/m
- 93, 120 dBiiWm
- 93. >3C dBuVfm
- 93. >40 OBuV/m
-93 ,^60 dBuV'm
- 9 3 . >6O dBuWm
• 95. >10dBuVJm
95, >2O dSuWm
• 95, »30 dBuVJm
• 95. >40 dBuV/m
Figure 8
Compiflaon of Apr-fl3 and Apr-94
° 93
— — 9 3
—<— 93
• loaBuvm
>20 OBuV/m
>30dBuV;m
—° 93. *40 dBuV/m
0 93
• - • • > • • 9 4
. - . « • - . 94
• • • ' • • - 9 4
. . . o - . . g^
. . . . . . 94
•• — • 94
^ 0 dSuV/m
>l0dBuV/m
>20 dBuV/m
>30 dBuV/m
>50 dBuVfm
>M OBuV/m
Figure 9
12 13 14 15 16 17 18 19 20 21 22 23
93,>IOdBijWm
93, >20 dBuVlcn
93, >30 dBuV/m
93. J O dBuV/m
93, >S0 dBuV/m
• " - • • 94. »20aBuV/m
- o - . . 94 ,40 dBLjVym
Figure 10
From the cumulative distribution data, it is also possible to extract values that could
help in defining the seasonal and year-to-year variations. These are shown in Table 4.
Seasonal
Variation
Jan-93
Apr-93
Jul-93
Jan-95
Apr-94
Jul-94
50% of time at
1900 h
>19dBnV/m
> 38 dBiiV/m
> 24 dBMV/m
>15.5dBMV/m
> 32 dBgV/m
> 23.5 dB^V/m
50% of time at
2100 h
> 23 dBuV/m
> 54 dBgV/m
> 26 dBpV/m
>15dBnV/m
> 48 dBpV/m
> 26 dBgV/m
50% of time at
2300 h
> 26 dBMV/m
> 60 dBpV/m
> 27 dBpV/m
>21.5dBgV/m
> 60 dBMV/m
> 29 dBMV/m
Table 4
Seasonal and year-to-year variation expressed numerically
This table shows numerically that the variations can be as large as 38.5 dB(jV/m at
2300 h and as low as 22.5 dBuV/m at 1900 h. This result, as with those given earlier,
indicates that a cumulative distribution on a yearly basis provides too limited information
for a good prediction of the field strength behaviour.
Interesting information can be extracted from the diurnal variation of the signal
levels. The maximum interference can be expected always in the late hours of the period
1600 - 2300 h, the diurnal variation being less distinct in July.
15
3.6 WORST-MONTH STATISTICS
Using predictions for annual statistics, Recommendation ITU-R PN.841 [5] gives
an expression to convert annual to the worst-month statistics :
where p w is the average worst-month time percentage of excess;
p is the average annual time percentage of excess;
Q is the conversion factor.
This allows us to make an additional comparison. From Rec. ITU-R PN.841, let us
assume that Q = 2.5 and then the expression above gives, for the worst-month, p w = 25%
if the annual time percentage of excess is 10%. Figure 11 shows a plot of the values of
field strength exceeded for 25 % of each month over a nine month period; also shown, is
the value of field strength exceeded for 10 % over the same period. The figure clearly
identifies April 1993 as the worst-month and confirms that a value of 2.5 for Q is very
appropriate for the data sample selected.
60
50
40
m
20
10
0
I
/
/
i k 1 i
\
• •• 1 - - t t —
* 1 5Month
• • • 1 1
^ i
25 % momhly value
to % value for the 9 monthpa lied
Figure 11
Worst-month over a nine month period
3.7 REPRESENTATIVE DAY
In order to get a better knowledge of the field strength behaviour, we derived from
the whule data base a representative day for each monlh. Firsl we calculated the median of
16
the field strength over a lime window of 60 minutes centred at each hour and then
computed the monthly median, upper quartile, and tower quartile for each hour.
Figures 12 to 14 show the median, upper and lower quartile variation of field
strength for each representative day for the three representative months chosen earlier.
The results confirm the behaviour described above of the diurnal and seasonal variability
of the potentially interfering signal field strength during evening hours.
12•o
7.00E+01 j-
6.00E+01 |
5.00E+01 }
4.00E+01 :
3.00E+01
2 OOF+fll
l.OOE+OI
0.00E+00 _ .
1700
1 - -
1800
Jan-93 Standard Day
, _ . .._
1900 2000 2100
Hours
. . - • • "
— — -
1
2200
,———
,
2300
Figure 12
7.00E+OI
6.00E+01
5.O0E+0I
« 3.00E+0!
2.00E+0!
1.00E+0I
I70O
Apr-93 Standard Day
, . , - - - ' . "
. . . \ ^ ~ ^ * ~ ^ ^' " _ — . . . • '
1800 1900 2000 2100 2200 2300
Hours
Figure 13
17
Jul-93 Standard Day
3.5OE+U I
3.00E+01
2.5(1E+OI i
| 2.00E+01
* I.50E+0I !
l.OOE+OI Ii
5 Wlli+OO i
o.ooE+nu i
I7(X) 1800 IWX) 2000
Hours
2!00 2200 2300
Figure 14
4. CONCLUSIONSThe data obtained from the experiment clearly indicate that higher values of field
strength were received than would have been predicted by well-known, established
prediction methods. This result could have serious consequences for the planning of VHF
broadcasting in the area since it is likely that the incidence of interfering signals, associated
with small time percentages typically from 10 to 1 %, will be underestimated by using the
existing prediction methods. These high values of field strength, which approach the free-
space level on many occasions, (and sometimes even exceed il), are due to the extreme
refractivity gradients which are frequently present in the region of west Africa,
From a critical analysis of the data and the graphs shown in this report, it is clear
that the annual average field-strength level predicted by the established prediction methods
is too limited. Seasonal variations, as well as diurnal variations, are not usually taken into
account in such prediction methods although the results of this study indicate that these
variations are, however, very important. For future planning of services, however,
especially in regions prone to significant seasonal variation, such variations should be
taken into account in order that prediction methods give realistic estimates of the signal
level to be obtained. This means that more accurate information, by season and hour, must
be acquired from experiments such as the one described here.
18
5. ACKNOWLEDGEMENT
The authors wish to thank Rohde & Schwarz and Deutsche Bundespost TELEKOM
for the equipment and for the help with its installation. The collaboration of SONATEL
and RTS (Senegal) is gratefully acknowledged for looking after the experiment and in
collecting the data. Finally, thanks are due to the BDT and BR of ITU for coordinating the
activities relating to this work.
I.H.S. has been partially supported under the agreement between ICTP and the
Centre for Turkish-Balkan Physics Research and Applications.
6. REFERENCES
[ ] ] CIA Factbook from http://www.ic.gov
[2] Recommendation 1TU-R PN.37O; VHF and UHF propagation curves for the
frequency range from 30 MHz to 1000 MHz
[3] GE89 - Final Acts of the Regional Administrative Conference for Planning of
VHF/UHF Television Broadcasting in the African Broadcasting Area and
Neighbouring Countries; Geneva, 1989.
[4] Radio-wave propagation measurements in Burkina Faso; K. Low and Z.
Bonkoungou; Telecommunication Journal, Vol. 57, XI, 1990,
[5] Recommendation [TU-R PN.841; Conversion of annual statistics to worst-month
statistics.
All the specific software designed to calculate cumulative frequency distributions
and related statistics are available from F. Postogna (e-mail : postogna@ictp.trieste.it).
19
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