NTIA Report 85-177

A Study of Interference Fields in a Ducting

Environment

George A. Hufford

Donald R. Ebaugh, Jr.

U.S. DEPARTMENT OF COMMERCE

Malcolm Baldrige, Secretary

David J. Markey, Assistant Secretary

for Communications and Information

June 1985

TABLE OF CONTENTS

LIST OF FIGURES

ABSTRACT

i v

1

1. INTRODUCTI ON 2

2. POSSIBLE APPROACHES TO MODELING

3.

4.

5.

2.1 Short-term Variability

2.2 Long-term Variability

THE MEASUREMENT PROGRAM

3.1 Automated Propagation Measurement System Equipment

Description

3.2 Paths

3.3 First-Order Results

ACKNOWLEDGMENTS

REFERENCES

iii

3

10

14

14

18

30

40

41
Figure

LIST OF FIGURES

Page

1. The density function of the Rayleigh decibel distribution. 4

2. Nakagami-Rice distributions drawn on Raleigh paper. The 6

parameter C is the constant-to-scattered ratio in decibels.

3. The interdecile range of the Nakagami-Rice distributions. 8

4. Distributions of the two-ray model drawn on Rayleigh paper. 9

The parameter B is the ratio in decibels of the two

amplitudes.

·5. Quantiles of deviations versus effective distance for the 12

maritime temperate climate over land. Adapted from CCIR

(1978a).

6. Block diagram for the receiver subsystem of the Automated 16

Propagation Measurement System.

7. Terrain profile: KEYT(3) to Cowles Mountain.

8. Terrain profile: KEYT(3) to Point Lorna.

9. Terrain profile: KABC(7, Mt. Wilson) to La Mesa.

10. Terrain profile: KABC(7, Mt. Wilson) to Cowles Mountain.

11. Terrain profile: KABC(7, Mt. Wilson) to Point Lorna.

12. Terrain profile: KOCE(50) to La Mesa.

13. Terrain profile: KOCE(50) to Cowles Mountain.

14. Terrain profile: KOCE(50) to Point Lorna.

15. Terrain profile: KTSC(8) to Boulder.

21

22

23

24

25

27

28

29

31

16. Cumulative distribution of the hourly median data obtained on 32

the path from KEYT(3) to Cowles Mountain.

17. Cumulative distribution of the hourly median data obtained 32

on the path from KEYT(3) to Point Lorna.

18. Cumulative distribution of the hourly median data obtained on 33

the path from KABC(7) to La Mesa.

19. Cumulative distribution of the hourly median data obtained on 33

the path from KWHY(22) to La Mesa.

iv
LIST OF FIGURES (Cont.)

Figure Page

20. Cumulative distribution of the hourly median data obtained on 34

the path from KLCS(58) to La Mesa.

2l. Cumulative distribution of the hourly median data obtained on 34

the path from KABC(7) to Cowles Mountain.

22. Cumulative distribution of the hourly median data obtained 35

on the path from KWHY(22) to Cowles Mountain.

23. Cumulative distribution of the hourly median data obtai ned on 35

the path from KLCS(58) to Cowles Mountain.

24. Cumulative distribution of the hourly median data obtained 36

on the path from KABC(7) to Point Loma.

25. Cumulative distribution of the hourly median data obtained on 36

the path from KLCS(58) to Point Loma.

26. Cumulative distribution of the hourly median data obtained on 37

the path from KOCE(50) to La Mesa.

27. Cumulative distribution of the hourly median data obtai ned on 37

the path from KOCE(50) to Cowles Mountain.

28. Cumulative distribution of the hourly median data obtained on 38

the path from KOCE(50) to Point Loma.

29. Cumulative distribution of the hourly median data obtained on 38

the path from KCTS(8) to Boulder.

v

A Study of Interference Fields in a Ducting Environment

George A. Hufford and Donald R. Ebaugh, Jr.*

In a cooperative program, the Federal Communications

Commission and the Institute for Telecommunication Sciences have

begun a study of the interference fields that may arise in a

ducting environment. This report gives some preliminary thoughts

on how enhanced signal levels might be modeled and describes a

measurement program that operated in Southern California.

Comparisons are made between some of the first-order statistics of

the data and two of the possible models and show that there still

remains a large gap between our modeling abilities and reality.

Key words: long-term variability; radio ducts; radio propagation; shortterm variability; UHF; VHF

1. INTRODUCTION

In some regions of the world, ducting phenomena are fairly common and

lead to interference at surprisingly long distances. To allow better spectrum

management, we need to be able to foretell on what propagation paths such

long-range interference is likely to happen. This information is essential in

managing the broadcast services and the mobile services when one must choose

frequency assignments, base station and transmitter locations, and permissible

radiated powers and antenna heights.

As a start toward satisfying this need, the Institute for

Telecommunication Sciences (ITS) has entered into a cooperative program with

the Federal Communications Commission (FCC) to acquire data related to these

phenomena, to assemble the resulting statistics, and to try to determine a

widely applicable model. A part of these efforts involves a measurement

program that originally observed received signal levels on long paths in

southern California. The paths extend from Los Angeles to San Diego and are in

a region well known for the persistent occurrence of super-refractive layers.

This report gives some preliminary ideas concerning the ultimate model,

describes some of the first-order statistics of the data obtained from the

measurement program, and provides a comparison of these statistics with

candidate models.

*The authors are with the Institute for Telecommunication Sciences, National

Telecommunications and Information Administration, U.S. Department of

Commerce, Boulder, CO 80303.
2. POSSIBLE APPROACHES TO MODELING

In attempting to describe the effect of the atmosphere on radio waves,

one very straightforward approach is to measure the refractivity structure and

then to trace rays or to perform a modal analysis for that structure. Such an

approach is actually used today as a real-time technique--by the Navy, for

example, to provide a better interpretation of radar returns (see Shkarofsky

and Nickerson, 1982), and by NASA to improve the accuracy of range finders.

The method is expensive and, as it turns out, still of questionable

accuracy. Its biggest drawback, however, is that it provides only a snapshot

of the conditions and cannot be directly used for planning purposes.

If we are to have a less expensive, more generally applicable method, we

must devise a model for the statistics of received signal levels. Actually,

we need two models: one to describe the atmosphere and another to describe

the effects of the atmosphere on radio waves. Since the first of these will

provide part of the input data to the second, it needs to model only those

characteristics of the atmosphere that the second model requires. On the

other hand, the second model should not require more data concerning the

atmosphere than can be conveniently modeled from meteorological

considerations. There is a tight interplay between the two.

There have been many attempts to provide suitable models of the

atmosphere. The most recent (and probably most promising) has been that of

Dougherty and Dutton (1981). In what follows here, we shall concentrate on

the second part of the modeling--the relationship between the atmosphere and

received signal levels.

Because the atmosphere changes at the whim of the notoriously hard-topredict weather, our only choice is to assume that the received signal level

on any particular path is to be considered a random process w(t). For future

convenience, we measure this in decibels relative to any desired level (1 mW, for

example, or 1 ~V/m--even the units used are not important for our purposes).

And we use the lower-case letter to indicate it is a random variable.

Statistics of the process will be indicated by upper-case or Greek letters.

It is customary to separate the signal level process into two

superimposed processes. One represents the small-scale or short-term

variability, while the other represents the large-scale or long-term

variability. The principal reason for this separation is that the two

normally arise from different physical causes. The short-term variability is

2
usually due to multipath fading--when there are two or more components of the

radio field that arrive at the receiving terminal by way of separate paths and

so add together vectorially according to their relative phases. The observed

variations with time come about because minute variations in the atmosphere

will change the electrical lengths of the several paths and so change the

relative phases. Long-term fading, on the other hand, is caused by wide-scale

changes in the atmosphere that affect the number and the magnitudes of the

multipath components. Since one expects gross changes in the atmosphere

during the course of the day, it is common to use the period of one hour to

distinguish the two processes. Thus, one also speaks of the within-the-hour

and the hour-to-hour variations.

In formal terms we may write

(1)

where wo(t) is a "smoothed" version of the received signal level (usually

"hourly medians") and the residual r(t) represents the small-scale

variations. As indicated by the lower-case letters, both components are to be

treated as random processes; Wo is measured in the same units as is w, and r

is measured in simple decibels. Since wo(t) will equal the local median

value, r will always have a median value of a dB.

The form of (1) implies a multiplicative relation for the corresponding

amplitudes or powers. This is by design. If the short-term variations are

caused by multipath, then they may also be callE!d "frequency-selective

fading." If at any instant we were to examine the received signal level over

a wide band of frequencies, we would find a very similar kind of variability

in which wo(t) provides an overall, general level. From the point of view of

the resulting frequency transfer function, it would be quite proper to

multiply the general level by a normalized random function of frequency.

2.1. Short-term Variability

In the case of short-term variability there are some simple

considerations that already allow us to reach fairly concrete results. These

considerations rest on the assumption that this variability is caused, as

stated above, by multipath fading in which the phases of received components

vary because of minute variations in the refractivity of the atmosphere.

Statistics of the short-term variability then depend only on the number of

components and on their relative magnitudes.

3
• 10 r-----.,--------r-----.....-----r-------..,.------,

-10 -5 0 5 10

S/Qnal-Io-medlan RallO. dB

-15

0.00 '=====:=t=--L-_---l --L L_--=::::d

-20

-

:: .05 t------+-----+----+-~---f------+\_---~

Q

et

Figure 1. The density function of the Rayleigh decibel distribution.

First, let us suppose there are many components, none of which

predominate. Then we have the case of Rayleigh fading (see, e.g., Rayleigh,

1894). The received signal is the vector sum of several voltages having

nearly the same amplitude but entirely random phases. The first-order

statistics (those that depend only on a single instant of time and do not

measure how rapidly the signal varies) satisfy the Rayleigh Law. For the

quantity r, the (complementary) cumulative distribution is given by the simple

formula

P [ ] = 2

-l0R/10

q = r r > R (2 )

We might call this the Rayleigh decibel distribution since the term "Rayleigh

distribution" is usually restricted to the distribution of the underlying

voltage amplitudes. Solving (2) for R we obtain the quantile

_ 9.n 1/9 R(q) - 10 £og 9.n 2 (3)

so that R(q) is the value that r exceeds for the fraction q of the time. Note

that this distribution has no parameters, a fact that makes it easy to use

since no measurements to determine parameters are necessary. It has a mean of

0.92 dB, a standard deviation of 5.57 dB, and an interdecile range ~r = R(O.I)

- R(0.9) = 13.40 dB. In Figure 1 we have plotted its density function--the

negative derivative of (2). The resulting bell-shaped curve is skewed toward

the negative values.

4
Of course, it is more common in the literature to introduce a nonzero

median as a simple parameter of the Rayleigh distribution. In our notation

this is done by simply adding that median to the right-hand side of (3); here,

this addition is taken care of already in (1) by the local median term WOo

When the multipath components do not satisfy the simple requirements for

Rayleigh fading, the next condition one can assume is that there are still

several components present but that one of them is much stronger than the

others. This condition leads to first-order statistics that satisfy what is

known as the Nakagami-Rice distribution (and also the Ricean or the II constantplus-a-Rayleigh ll distribution; see, e.g., Norton et al., 1955). Aside from

the median (which here we shall want to assume vanishes), it has one parameter

that can be represented as C, the IIconstant-to-scatteredll ratio measured in

decibels. This is the ratio of the power in the single strong component (the

IIconstantll component) to the average power in the sum of the remaining

components (the IIscattered II component). It is interesti ng to note that,

except for a slight change in meanings of the variables and parameters, the

Rayleigh distribution is equivalent to the chi-squared distribution with two

degrees of freedom. Similarly, the Nakagami-Rice distribution is equivalent

to the IInoncentralll chi-squared distribution wHh two degrees of freedom.

Both of these distributions are described in, e.g., Abramowitz and Stegun

(l964), and computer programs to calculate values may be found in some of the

available libraries of mathematical or statistical functions. In any case,

however, statistics of the Nakagami-Rice distribution are hard to compute and

they depend on the parameter C in a nontrivial way.

In studies of short-term variability, it is customary to plot observed

cumulative distributions on IIRayleigh paper. 1I This is graph paper in which

the ordinate represents the received signal level scaled linearly in decibels,

and the abscissa represents probability (or fraction of time) scaled

nonlinearly according to the negative of the right-hand side of (3). If a

distribution satisfies the Rayleigh Law, then it will appear on Rayleigh paper

as a straight line with slope -1.

On the other hand, if we used Rayleigh paper to plot the Nakagami-Rice

distribution, we obtain results such as those portrayed in Figure 2 where the

several curves correspond to several values of the parameter C. The most

5
""

r-.

t-- --....::

r---::::::t::: 20 r--

r-------r--- 0--.. C = 15 dB

f-... -

--- I

r------1O

i'--

'\ ~$

~O~ ~,~%'\

-30

-25

.

o -10

o

-5

10

....

c:

Cll

-15

<II

o

...

.

-20

c:

0-

If)

-35

-40

.001 • 1 .5 .8.9 .97

Probability

.99 .997 .999

Figure 2. Nakagami-Rice distributions drawn on Rayleigh paper. The

parameter C is the constant-to-scattered ratio in decibels.

6
striking thing about these curves is that they all look like straight lines;

so much so that replacing them by straight lines appears to be a reasonable

approximat ion.

Now as it happens there is a distribution used in the theory of

reliability known as the Weibull distribution, which may be most simply

defined as one that plots out as a straight line of arbitrary slope on

Rayleigh paper (Weibull, 1951). It seems very appropriate, then, to use this

distribution as an approximation to the Nakagami-Rice distribution, the point

being that many of its characteristics are easy to compute. If the slope

equals -a, then the quantiles are easily detemdned from (3) as

R(q) = a 10 ~og ~n 1/9 in 2 (4 )

As with the Rayleigh distribution, we should probably call this the Weibull

decibel distribution, since the usual definition is in terms of the

amplitude. The mean, standard deviation, and interdecile range are all equal

to the Rayleigh values multiplied by the slope a. Since the relation here is

so simple and since the slope of a cumulative distribution is one measure of

the "concentration," one may as well replace a as the parameter of the Weibull

distribution by either the standard deviation or the interdecile range, both

of which may have more immediate meanings. In what follows, we shall normally

prefer the interdecile range 6r as the most convenient of these measures.

To remain within the range of the Nakagami-Rice distribution, the value

of a should be restricted to lie between 0 and 1. At the extreme a = 0, we

have a simple jump distribution in which r(t) = 0 with probability 1. This

corresponds to the case where there is only the isolated single component, the

others having vanished. At the other extreme, a = 1, we have the Rayleigh

distribution again; here, the isolated component has vanished. For

intemediate values there will be a nontrivial relation between the parameter

C of the Nakagami-Rice distribution and the slope. In Figure 3 we have

plotted the interdecile range of the Nakagami-Rice distribution versus C.

This plot is, however, of only incidental interest since from a

phenomenological point of view it is immaterial which of these related

parameters we use and the interdecile range is certainly the easier to measure

and to employ in further computations.

7
15

.

Ql

10

Ql

-

-----... --

"'" -----~----

'------r--

o

-10 -5 o 5 10 15 20

Cons lanl - lo-scal lered Ral /0. dB

25 30

Figure 3. The interdecile range of the Nakagami-Rice distribution.

There is one other model of the first~order statistics of short-term

variability that is sometimes mentioned in the literature (see, for example,

Dougherty, 1968). Called the two-ray model, it assumes there are just two

components in the multipath field with relative phases that are uniformly

distributed over the whole circle. The resulting quantiles (in decibels) are

given by

R(q) = 10 ~og(l + 2S cos 'TTq)

+ S2

(5 )

where S is the (voltage) ratio between the amplitudes of the two components.

In Figure 4 we have plotted a few of these distributions on Rayleigh paper

using the parameter B = 20 log S. In addition to flattening out in the tails,

these distributions all show a strong downward curvature at central values.

We might note that when B vanishes (so that the two components have equal

magnitudes) the interdecile range is 16.01 dB. This is therefore one example

of a distribution with a steeper average slope than that of the Rayleigh

distribution. The difference, however, is small and when B exceeds only

2.5 dB, it vanishes.

Experience has shown that in the great majority of cases the NakagamiRice distribution (and especially the limiting case of the Rayleigh

distribution) does indeed portray fairly accurately the observed first-order

statistics of short-term fading. Until other distributions, such as that of

8
.8.9 .97 .99 .997 .999

Probablll/Y

• 1 .5

i' I "

" I

" I

" I

~"i"'"--

:--

I"

--- 10

~" "-

"\: ~~",~.l. , ~J'

, ,91

\~ " " B = 3 dB

",

'"

,

"

",

"

\ ""--- " 1

" <P

"

"'" 1\ \\

"

"

I

"

\

\

-40 \

.001

-35

-30

10

-25

. -10

-5

o

5

....

c:

-15

I

Q

....

I

·-20

§,

II)

Figure 4. Distributions of the two-ray model drawn on Rayleigh paper.

The parameter B is the ratio in decibels of the two amplitudes.

9
the two-ray model, are shown to be of importance, we would propose to model

these statistics with this one set of distributions and, further, to replace

them by the more easily managed Weibull approximations.

2.2 Long-Term Variability

We have seen, then, that within each hour the first-order statistics can

be characteri zed by two parameters--the medi an and the i nterdecile range M.

From hour to hour we would suppose that both parameters will vary and so we

are led to consider two slowly varying random processes, wo(t) and L\r(t),

whose statistics are those of the long-term variability. Our first concern

will be for the first-order statistics of these processes; but note that we

would expect the two to be statistically dependent and also that they probably

have diurnal and seasonal trends.

To study these statistics, we seem obliged to resort to an empirical

study of measured data. Our present state of knowledge does not permit us to

do much more, although certainly any modeling of the phenomena should take

account of whatever we do know. There have been very few previous

measurements of the within-the-hour interdecile range and an attempt to model

its statistics must wait on the acquisition of a body of data. We turn here

to a discussion of the hourly median.

Of past attempts at modeling long-term variability, probably the most

widely used method is that suggested by Rice et al. (1967). It forms a part

of the ITS Irregular Terrain Model (see Longley and Rice, 1968; and Hufford et

al., 1982) and of a Comite Consultatif International des Radiocommunications

(CCIR, 1978a) approach. In this method one writes

(6 )

where Wref is a "reference" level and v(t) is a "deviation." The reference

level is meant to be the fixed signal one would obtain with a "normal"

atmosphere--i.e., a hydrodynamically unstable (hence turbulent) atmosphere

where the refractivity follows a fixed exponential decrease with increasing

altitude. The deviation then forms a random process, and there is nothing new

here. The important step, however, is to assume that the first-order

statistics of the deviations can be described in terms of only two

parameters--the "climatological type" and an "effective distance." The

climatological type can be one of some eight discrete types ranging from

"equatorial" to "po l ar." The effective distance is a function of actual

10
distance, frequency, and antenna heights; it is a normalized distance that

attempts to put all paths into a common mold. In practice, one speaks of the

median V(0.5) and of the quantiles of the deviations--which are now denoted by

y(t)--from this median. In Figure 5, we show the curves of these quantiles

versus effect ive di stance for the case of the II mar itime temperate over 1and ll

climate. Except for the design of the effective distance, such curves are

entirely empirical; they have been drawn through measured values that exhibit,

unhappily, a rather large spread.

Nevertheless, the method performs fairly well. This is attested to in

the report by Longley et al. (1971), which summarizes data from a large number

of paths and compares the observed cumulative distributions of hourly medians

with those provided by this method.

The method was originally prepared to treat the case of those paths over

which the dominant mode of propagation is tropospheric scatter. It was then

extended to include shorter paths. Ducting phenomena, however, have never

been satisfactorily included. In Figure 5, there are some large upswings at

large effective distances for the very low percentiles. This represents an

attempt to describe the enhanced fields that arise, presumably, from the

presence of ducts. But thi s refers to the IInorma 111 antenna towers in the

presence of the IInormalll duct heights that appear in a maritime temperate

climate--which probably means the North Sea since that is the region used to

epitomize this climatological type. There is no attempt made to allow for

other situations. In general, we would suppose that pegging the enhanced

fields caused by ducting to the II reference ll level can never be satisfactory.

The method just described tries to portray the entire range of time

variability. A second method--one that concerns only the enhanced fields

present for very small fractions of time--was first suggested by Misme (1974)

and is now a method given by the eeIR (1978b). It speaks of a "1 eakage

coefficient" into and out of a presumed duct and of a II minimum coupling

distance" into the duct. It gives a formula for the attenuation relative to

free space directly without the mention of a reference level. The formula is

most obviously a function of the path length but the coefficients involved

depend on the average initial lapse rate of refractivity, the frequency, the

terrain irregularity parameter .6.h, and the proportion of the path that lies

over sea. The method is designed for quantiles of 1% or less and for

frequencies between 600 MHz and 15 GHz.

11
./V

¥ ~I---

! / I ~I I //V I 1 1- 1///V- I I

II I

I

Y!/ I I 10

, I I I !J

k l I

I

I ! 50 I I I

~I I I 90 I I I I

~I J- I 99

99,9 I I I

I~I I 99,99 i I I !

I ' !

, I L--I I

I I

I I

I I I

60

30

50

70

40

80

-20

-50

o 100 200 300 400 500 600 700 800 900

Effective distance~ kiZometers

-40

-30

-10

Figure 5. Quantiles of deviations versus effective distance for the

maritime temperate climate over land. Adapted from CCIR

(1978a) .

12
This approach has many of the features that seem desirable to us; the

limitations seem severe but could probably be relaxed with further study. On

the other hand it seems a little artificial to use the average initial lapse

rate of refractivity to categorize the incidence of ducts and their

characteristics--other climatic parameters would probably be more suitable.

Another parameter that is missing from the method is the antenna elevation and

how it relates to the possible duct elevation; this seems important to us.

In general, we would expect signal levels in the presence of a duct to

depend on the depth, strength, and extent of the duct and on the radio

frequency and the path geometry. Thus, the statistics of signal enhancement

will depend on these factors and on the frequency of occurrence of ducting

layers. Path geometry is important because it is at grazing incidence upon a

ducting layer when effects are most pronounced. As the ray elevation angle is

increased from 0° to perhaps 5° (about 85 mrad) the effects become

negligible. Enhancements can be as great as 40 dB above the long-term median

for transhorizon paths. On line-of-sight paths (perhaps 50 km long) signal

levels 6 dB above free space are not unknown.

If a radio transmitting antenna is above a horizontal ducting layer, the

usual effects are multipath fading and extended range while radio holes and

antiholes may also occur. If the transmitter is within the layer, extended

range occurs along and below the layer so that if both transmitter and

receiver are within the layer, an enhanced signal level may exceed the free

space level for great distances. This can happen because within the duct

there is an inverse distance dependence, while in free space the decrease in

signal level is proportional to the square of the distance. If an elevated

layer is very much above the normal path of a radio ray, the duct will have

little, if any, effect on propagation losses.

With these considerations in mind, we would suppose that a good, widely

applicable model of signal level statitics on a given path would:

(1) postulate a small number of atmospheric conditions including

"normal" atmosphere and atmospheres containing ducts of various

characteristics

(2) calculate statistics of signal levels for each of these

atmospheric conditions

(3) mix these "mo des of propagation" according to the frequency of

occurrence of each of them in the region involved.

13
To support such a model it might be sufficient to know simply the frequency of

occurrence of surface-based ducts and the frequency of occurrence of elevated

layers, this latter to be supplemented with a probability distribution of

layer elevations.

3. THE MEASUREMENT PROGRAM

Accompanying our attempts to model signal variability in a ducting

environment is a measurement program that uses specially constructed receiving

systems to measure and record signal levels from IIsignals of opportunity.1I

These systems were put into service in the San Diego area in September 1981.

The transmitters to which they were tuned were mostly television transmitters

4n the Los Angeles area about 180 km to the northwest. The systems remained

there until August or November 1983, thus giving us what appears to be about 2

years of data. Unfortunately, there were extensive down times and the

resulting records are very spotty.

One of the systems was subsequently taken to Boulder, Colorado, and put

into service in February 1984. It has since been recording data from a single

television station in Pueblo, Colorado, about 190 km to the south.

We want here to describe the equipment used, the propagation paths for

which signal levels were measured, and some first-order statistics that were

obtained.

3.1 Automated Propagation Measurement System

Equipment Description

The automated propagation measurement system is a special-purpose,

microprocessor-controlled receiver. Its function is to receive and record the

levels of up to 10 signals in the VHF and UHF ranges for long periods of

time. The system tries to fill the need to be able to collect long-term radio

propagation data while demanding only a small amount of routine maintenance.

The system includes the important features of se 1f-ca1i brati on under full

control of the microprocessor and self-restart following a power failure.

Near the end of each hour the system will print a summary of the data

collected during that hour. The summary gives a number of points on the

received signal level distribution for each of the programmed frequencies. In

addition to these statistical data some selected values from the calibration

process for the current hour are printed. Finally, all of the signal level

data collected during the hour, all of the calibration information, and some

necessary bookkeeping data are written onto magnetic tape. The routine manual

14
maintenance, therefore, involves changing the computer terminal paper and the

magnetic tape.

The measurement system is composed of two major subsystems--the receiver

and the microprocessor. The receiver subsystem, shown in block diagram format

in Figure 6, includes components such as the antennas, the antenna control

box, the local oscillator (a commercial frequency synthesizer), and the

receiver chassis itself (a five-plug-in module device). The microprocessor

subsystem is physically divided into several components including the digital

tape deck, the computer terminal (keyboard and printer), and the

microprocessor chassis. There is one more component of the microprocessor

subsystem, and it is probably the most important component of the entire

system--the software programs. These not only control all of the functions of

the system, but also digitize and record the received signal level data.

Signal energy enters the receiver via one of three receiving antennas.

These are connected to an antenna calibration box located nearby at the top of

an antenna tower. Particular antennas used are chosen and aimed to acquire

the signals from the particular desired signals. For the San Diego

measurements the most often used was a horizontally polarized log-periodic

antenna with a frequency range from 150 to 1000 MHz. Antennas for the

remaining two positions varied with the particular receiver site. Two

examples are a yagi tuned to 868 MHz, and another yagi tuned to TV channel 3

at 60 MHz. Proper antenna polarization depends, of course, on the source.

During propagation measurements, the antennas are connected through the

antenna calibration box directly to the receiver input. During a calibration

period, a switch disconnects the antennas and substitutes a broadband noise

source. This provides a known signal level across all measurement

frequencies. Since the noise diode calibration signal passes through exactly

the same signal path as the received signal, this technique accurately

compensates for all features of the signal path--regardless of the amount of

attenuation or gain present in a given channel. The only uncalibrated parts

of the signal path are the antennas themselves and the short lead-ins between

antennas and calibration box inputs.

Most of the remainder of the receiver is contained in a series of modules

that fit into a commercial instrument chassis. The signals first pass through

a signal-conditioning module where the desired signals are separated from

other frequencies with rf bandpass filters (typically 20 MHz wide) and

15
AnI. 1 Ant. 2 Ant. 3

Optional -EManual Controls

Il

SIGNAL CONDITIONING --1-----,

[ sw, ] -'OdB

\ INTERFACE

CALIBRATION

150MHz

Xtal

Osc.

loverioad

lOG AMPLIFIER L

Log Video .--------,

Log Amplifier ~-..... 100 dB

RECEIVER

I Broadband

Detector

10-1000MHz

Figure 6. Block diagram for the receiver subsystem of the

Automated Propagation Measurement System.

16
amplified with low-noise preamplifiers. The exact bandpass filters used will

vary with the frequencies selected to be received at each site, and therefore

the module is constructed so as to allow easy replacement. In Figure 6 the

switch SW1 is a very long-life mechanical rf switch that has a high insertion

loss and should resist possible intermodulation products from strong out-ofband signals. The rf switch SW2 is a simple PIN-diode switch that can be used

here because insertion loss and intermodulation performance have already been

assured by the preceding signal conditioning.

The receiver module is a single-conversion, superheterodyne receiver with

a 21.4 MHz IF frequency. A final bandpass of 2 kHz provides a measurement

noise floor at about -118 dBm. Meaningful output from the system presupposes

well-known and stable source transmitter frequencies. Part of the rf signal

is split off for a broadband detector. This detector senses the total power

in the rf band-pass and indicates a possible overload problem if too much

signal power is present. The receiver frequency is precisely selected by the

local oscillator frequency, which is provided t~ a commercial frequency

synthesizer. The output of the synthesizer is amplified to +22 dBm for highlevel mixing to reduce the susceptibility to intermodulation products.

The IF signal is converted to a DC voltage by the logarithmic amplifier

module with a 100 dB dynamic range. Operation over this very large dynamic

range assures accurate measurements even if input signal amplitude changes

over a very wide range. The logarithmic amplifier module also contains an

audio amplifier and a loudspeaker, which may be useful for diagnostic

purposes.

The calibration module contains a 150 MHz signal source and a 120 dB step

attenuator. These provide a known calibration signal over a -20 to -140 dBm

range and will characterize the log amplifier response in 10 dB steps.

The entire receiver can be controlled manually or automatically via a

computer program. When the receiver is being Llsed for measurements, it will

normally be under computer control. Testing and trouble-shooting are often

easier under manual operation. Many of the manual controls are located on the

digital interface module. Other controls are positioned on the modules that

they control.

The module chassis contains power supplies and interconnection wlrlng

used by the modules. Most of the IF and rf signal paths go through coaxial

17
cabling on the front panels of the modules, because the connectors on the back )

of the modules are not designed to handle radio frequencies.

A high-accuracy frequency synthesizer is the last major subassembly of

the measurement system. This instrument generates the required local

oscillator (LO) frequencies, as commanded by the computer via an IEEE-488 data

bus. The synthesizer is a standard instrument, although an internal jumper

has been positioned to speed up tuning and accuracy at the expense of some

(unused) modulation capability.

Amicroprocessor-based control and analysis system operates the

receiver. Under the control of measurement programs stored in ROM (Read Only

Memory) and magnetic bubble memory, the receiver is cycled through a

preestablished sequence of measurement frequencies, using proper antennas and

signal-conditioning paths. At the beginning of each hour a complete system

recalibration is accomplished with a combination of calibration techniques

involving the noise diodes and the 150 MHz calibration oscillator. These

frequent calibrations should keep the signal level measurements accurate in

the face of possible system gain drift.

Laboratory testing of the receiver system with known signal inputs

indicates that the recorded signal level can be up to 4 dB away from the

signal level injected at the antenna calibration box. The magnitude of error

is more pronounced when low-level signals are being monitored. For example,

the widest discrepancy between actual signal level and recorded signal level

occurred in a test at 687.24 MHz. A -90 dBm signal was injected at the

antenna calibration unit, and statistics of its measured level were recorded

in the automatic measurement mode over a standard 50-min test cycle. While

the record showed a signal level greater than -90 dBm for more than 99% of the

time, it also indicated a level greater than -86 dBm for 5% of the time.

Hence, one should keep in mind that some degree of error, perhaps up to as

much as 4 dB, may be associated with much of the automated propagation

measurement system data.

3.2 Paths

There were somewhat more than 30 paths whose signals were used for this

progr~. Of these we would like to describe here 14 that are interesting for

our purposes and for which we seem to have a useful number of valid data.

The three San Diego receiver sites were located in three rather different

local environments. The first was at the FCC Field Office located in a five18
story building in La Mesa, a suburb on the northern edge of San Diego. The

second was part of a small antenna farm on Cowles Mountain, a small mountain

(477 m high) northeast of La Mesa. And the last receiver site was on Point

Lorna, a United States naval reservation on the Pacific Ocean at the

northwestern corner of San Diego.

The transmitters were all "signals of opportunity" derived from

television stations. Now, the use of television transmitters as signals for

propagation studies has its advantages and its disadvantages. Among the

advantages are high radiated power, very good frequency stability, and a

sharply localized spectrum. A UHF television station will often have an

effective radiated power (ERP) of as much as 5 MW and almost all of this power

will be localized in the video carrier. There are, however, at least two

disadvantages. First, a station is not normally in operation for the full 24

hours of the day and there will be regular gaps in the record. Indeed,

operating hours for some of the stations observed in the present program were

rather short. The second concern is with the antenna patterns. These may be

omnidirectional in that they radiate equally in all azimuthal directions, but

they are almost always high gain antennas with a sharp beam in the vertical

plane. Beam widths can be 2° or even less. If an antenna is on a mountain

overlooking the area to be served, it will often employ electrical beam

tilting and direct the beam downward by 1° or 2° toward the desired service

area. Since we are interested here in interference fields where elevation

angles to shielding terrain obstacles may be out of the ordinary and where a

layered atmosphere may bend the rays in unusual directions, it is therefore

difficult to say how one should treat these narrow beams. In particular, it

seems questionable whether one can immediately transfer results obtained by a

study of such television transmitters to the case of the mobile services where

lower gain antennas are normally used.

The paths extend along the California coast between Los Angeles and

San Diego, and they are subjected to a radio climate dominated by what is

called the "marine layer." This is a layer of marine air trapped by a

temperature inversion that extends along the coast and out into the Pacific

Ocean. Its depth undergoes considerable variabiliy with an average near Los

Angeles of about 500 m. Accompanying it there often appear one or more superrefractive layers that may then affect radio waves. Winter storms, of course,

will blow away the marine layer leaving only a "normal" atmosphere.

19
3.2.1 KEYT(3), Santa Barbara

Although the principal purpose of the program was to measure UHF signals, ,

we did observe a few VHF stations. One of them, KEYT(3), operates at the

particularly low frequency of 61 MHz. It was made part of the program because

of a particular need of the FCC to study the effects a proposed San Diego

based Channel 3 station would have on the environment.

The station is network affiliated, radiates maximum permitted power, and

normally operates from 0600 to 0100 local time. It serves Santa Barbara and

the adjacent coastal cities some 140 km northwest of los Angeles. The antenna

is on TV Peak in the Santa Ynez Mountains at an altitude of 1324 m. It should

be above the marine layer most of the time.

The station was received at both Cowles Mountain and Point lorna. In

Figures 7 and 8 we show the terrain profiles of the two paths. Note that they

can both be characterized as long (330 km) oversea paths with horizons on the

water.

3.2.2 KABC(7), KWHY(22), and KlCS(58); Mt. Wilson

These three television transmitters are all located in the antenna farm

on Mt. Wilson northeast of los Angeles. Their widely separated carrier

frequencies should provide us the opportunity to describe directly how

received signal levels vary with frequency.

KABC (175 MHz) is network affiliated, transmitting maximum permitted

power. It is another of the VHF stations observed. Its normal operating

hours are from 0530 to 0330, and this station is the most nearly continually

operating of all the broadcast stations observed. It was received at all

three San Diego sites.

KWHY (519 MHz) is an independent ~tation that operates as a subscription

television station using a scrambled signal in the evenings. It transmits

maximum permitted power and normally operates between the hours 0630 and

2430. It was received at both la Mesa and Cowles Mountain.

KlCS (735 MHz) is a public television station operated by the los Angeles

Unified School District. It transmits at nearly the maximum permitted power;

unfortunately, its operating hours are rather short, from 0730 to 2130 and

even less on the weekends. It was received at all three receiver sites.

The three antenna towers are all very close together almost 1800 m above

sea level. The eight paths involved (examples of which are shown in Figures

9, 10, and 11) are all very similar. They are about 185 km long, but because

20
ooסס1

8000

11\

ClI

...

!

4000

2000 '

.-1.370

(3)

150 200

Kllomelers

SOUTHERN CALIFORNIA

Sea Ie - 1/2500000

300

331.2

COWLES MTN

Figure 7. Terrain profile: KEYT(3) to Cowles t1ountain.

21
ooסס1

Kllomefers

8000

6000

4000

2000

150 200

o

o

KEYT (3)

SOUTHERN CALIFORNIA

325.5

PT LOMA

k= 1.374 Scale- 1/2500000 VerI E,aQ.- 25/1

Figure 8. Terrain profile: KEYT(3) to Point Lorna.

22
3000

2500

2000

VI

....

1500

!

(7)

Kilometers

188.3

LA tvESA

k -1.345

SOUTHERN CALIFORNIA

Sea Ie· 111500000 Vert ExaQ. - 50/1

Figure 9. Terrain profile: KABC(7, Mt. Wilson) to La Mesa.

23
3000

2500

2000

( 7)

Kilometers

SOUTHERN CALIFORNIA

Sea Ie - 11\500000

183.9

COWLES MTN

VerI E'aq.- 50/1

Figure 10. Terrain profile: KABC(7, Mt. Wilson) to Cowles Mountain.

24
1000 .

~·1.354

( 7)

K,lomelers

SOUTHERN CALIFORNIA

Scale- 1/15(~OOO

189.1

PT LOMA

Figure 11. Terrain profile: KABC(7, Mt. Wilson) to Point Lorna.

25
of the high transmitters they are all line-of-sight or nearly line-of-sight

paths. The paths to Cowles Mountain are, indeed, line-of-sight. Those to

La Mesa are interrupted by a mountain ridge about 9 km in front of the

receiver, and those to Point Lorna by a local hill only 0.6 km in front of the

receiver. Note that if we postulate a marine layer 500 m high, then rays

emerging from the transmitter will be tangent to that layer at a distance of

about 145 km. This would be from 40 to 50 km in front of the receiving

terminals.

3.2.3 KOCE(50), La Habra

KOCE(50) is a public television station operating at 687 MHz and with

maximum oermitted power. Its normal operating hours are from 0530 to 2400.

Although it serves Huntington Beach, its transmitter is about 30 km away in

the Puente Hills overlooking La Habra. These locations are in the southern

part of the Los Angeles area and, indeed, the station probably reaches most of

the communities there. The antenna is 469 m above sea level which is well

within the range of elevations assumed by the top of the marine layer.

Although somewhat inland, the antenna should be above the marine layer some of

the time and within it at other times.

The station was observed at all three receiver sites and the resulting

path profiles are shown in Figures 12 to 14. The paths are long (about

155 km) and are interrupted by some low mountains at about midpath. The path

to Point Lorna is largely over the sea, but the two horizons are both on land,

the one near the receiver being a local hill only 0.5 km away. The three

paths show quite a number of differences, and this, coupled with the behavior

of the marine layer, should make the results very interesting.

3.2.4. KTCS(8, Pueblo) to Boulder, Colorado

This is the path that resulted when one of the receiver systems was moved

to Colorado. The radio climate in this new location is greatly different. In

Colorado the air is thin and dry and super-refractive layers are a rarity.

The receiver was in an ITS laboratory in a one-story wing of a building

near the southern edge of Boulder. The transmitter is a VHF television

station (181 MHz) operating at maximum permitted power. It is a public

television station with normal operating hours from 0600 to 2300.

Unfortunately, in the summer it goes to a reduced schedule and is on the air

only from 1400 to 2300.

26
2000

1750

1500

1250

1/1

'-CIl

.... 1000

!

750

Kilometers

(50)

158.0

LA tv£SA

k'I.352

SOUTHERN CALIFORNIA

Scale- 1/1000000

Figure 12. Terrain profile: KOCE(50) to La Mesa.

27
1/1

•'"...

K/lomefers

(50)

SOUTHERN CALIFORNIA

154.3

COWLES MTN

al. 351

Figure 13. Terrain profile: KOCE(50) to Cowles Mountain.

28
1250

K,lomelers

(50)

100

158.9

PT LOMA

-\ .360

SOUTHERN CAL. IFORN IA

Sea Ie· III 000000

Figure 14. Terrain profile: KOCE(50) to Point Lorna.

29
The terrain profile is shown in Figure 15. The path runs through the

plains of eastern Colorado parallel to, but not far removed from, the Rocky

Mountains. The peak in the middle of the path is one of the foothills that

happens to intrude. The actual horizon for the receiver is a small hill about

9 km away.

3.3. Fi rst-Order Results

With the kind of measurements being obtained we would suppose that there

are many sorts of analyses that might be usefully developed. As we pointed

out before, however, the data are very spotty and of mixed quality so that

analyses are difficult to make and when made they would be difficult to

interpret. For example, the two seasonal extremes, in February and August,

seem greatly underrepresented in the data and whether one should (or even

could) make suitable allowances requires consideration.

We have chosen here to make only a simple first-order analysis in which

we have lumped together into an individual statistical ensemble all available

data for each path. In Figures 16 through 29 we have plotted the resulting

cumulative distributions of the hourly medians of attenuation relative to free

space. Included on those graphs are predictions given by the two methods

described in Section 2.2. We have called them, but only for convenience, the

ITM (as demonstrated in Figure 5) and the CCIR methods. Note that the latter

tries to predict only for 1% or less of the time, and that is why it appears

as a short segment on the left side of a graph.

Some of the predictions given here, such as the two in Figure 24, are

remarkably accurate; some, such as those in Figure 27, are so-so; but many are

very different from the measured data. We have, of course, the problem of

spotty data and the uneven representation of diurnal and seasonal periods, and

perhaps a more consistent and extensive set of data would have produced quite

different measured curves. But more generally, we should not be surprised

that prediction and data differ, for the environment here is far different

from the "norma1" envi ronment envi saged by the models and, especi ally, the

path parameters used here are often outside the professed ranges. For

example, the CCIR method has been developed only for fairly high frequencies,

and while we have therefore not attempted to use this method for the TV

Channel 3 data in Figures 16 and 17, we have, to the contrary, struggled to

extrapolate the curves back to frequencies for Channels 7 and 8.

30
4000-

3500

3000

1/1

2500

!

2000

1000

o

KTSC[81

." 1 .20">

.~~~"';"";.J....;..!c.:..:...:...:..:"'"

100

Kllomelers

EASTERN COLORADO

Sc a Ie· 111500000

190.0

BOULDER

Figure 15. Terrain profile: KTSC(8) to Boulder.

31
- r--- __

-- ,

"-

"-

"- \.

r\ "-

"-

"-

"- .."

"- ....... ....... I'., .......

- ....... ....... .......

KEYTl3J 10 Cowles MIn ........

f- 2255 hours r-- ....... .......

measured

--- I- \ ....... ---- ITM ....... .......

I I r\ t--- .......

.......

o

.

c: 20 o

40

50

.01 10 50

Percent T,me

90 99.99

Figure 16. Cumulative distribution of the hourly median data obtained

on the path from KEYT(3) to Cowles Mountain.

o

20

.

c:

o

...

III

40

Ql

...

...

'q:

50

I I

t'-

"- KEYTl3J 10 PI Loma _ ..... , 5689 hours

"-

~" measured -

---- ITM

"

" "- 0- " ..., " ........ ..I",. ,

' ..... r-" " ""l.

1'-- ........ r,.,

t-- 'L.. .......

.01 10 50

Percent T,me

90 99.99

Figure 17. Cumulative distribution of the hourly median data obtained

on the path from KEYT(3) to Point Lorna.

32
..I""""'------,

1"- __ .. .. ..

-- -- I'--<,.....,.., -- ""l.-

-- -- --,

r---t. -- Il- -- -- 1-- __

-- -- -- L-

-- r-_

KABel71 --- -- f--

10 La Mesa -- -- -- 3760 hours --- --- measured f----- ---- ITM

...... CCIR

I I

o

c:: 20

()

40

60

.01 10 50

Percen t T,me

90 99.99

Figure 18. Cumulative distribution of the hourly median data obtained

on the pa th from KABC (7) to La Mesa.

50 90 99.99

Percent T,me

10

r

KWHYl22l 10 La Mesa

3647 hours -

measured

- - ---- ITM

~'---L - ...... CCIR

I'--

-- ........ -,

-- ....r---. -- .... -....'L...- 1'--- "l....-h- -- ..... I~

.. -- .... -- .. "'- .....

-- .. -- -- ---- -- - "'-- -- r_ -- ---

40

60

.01

. 20 ....

o

--l1J

::)

c::

(ll

--

"t--

Figure 19. Cumulative distribution of the hourly median data obtained

on the path from KWHY(22) to La Mesa.

33
I I

KLCS(58J 10 La Mesa

1798 hOurs -

measured

---- ITM - ...... CCIR

- .............. .......

" ....... .......

-~....... ........ ............ ....... ............ r.f""1...- ~-

-- It- ....... '----t. -- -\ -- -- 1\ ... --- - ....... - -- -- --- '-----

o

.

c: 20 ()

....-

III

:;)

c:

III

....

....

'q

40

60

.01 10 50

Percent T,me

90 99.99

Figure 20. Cumulative distribution of the hourly median data obtained

on the path from KLCS(58) to La Mesa.

~;-;-.. ....- .. -~

1'-1..,... --- - - - -- -- It- --- ---- rt-- - -- \- -- """'-L -

I'<-,

.........

KABC(7J 10 Cowles MIn

4395 hours

measured

I- ---- ITM

...... CCIR

I I

o

c: 20 ()

40

60

.01 10 50

Percent TIme

90 99.99

Figure 21. Cumulative distribution of the hourly median data obtained

on the path from KABC (7) to Cowl es r10unta in.

34
f- ----- f--- __

- -;0..

- f-_

-- - --- 1-_-- ---

iL-l'--

t""Ih h

I'---Lr---

KWHYl22J 10 Cowles MIn

857 hours

measureC1

---- ITM

...... CCIR

I I

o

t: 20

o

40

60

.01 10 50

Percent Time

90 99.99

Figure 22. Cumulative distribution of the hourly median data obtained

on the path from KWHY(22) to Cowles Mountain.

I

f- ----- 1--- __

...... --I- - .......I'------ - t---

~-- -- - - -- 1- ___

r--o-h ---

-,.

KLCS(58J 10 Cowles MIn

i\ 2166 hours

measureC1

1\ ---- ITM

...... .. CCIR

r....

\

o

t: 20 o

40

60

.01 10 50

Percent Time

90 99.99

Figure 23. Cumulative distribution of the hourly median data obtained

on the path from KLCS(58) to Cowles Mountain.

35
.

c: 20 Cl

....-

lI:J

:J

c:

III

....

....

"t

10 50

Percent Time

90 99.99

Figure 24. Cumulative distribution of the hourly median data obtained

on the path from KABC(7) to Point Lorna.

o

.

c: 20

Cl

40

I J

KLCS(58l to Pt Loma

3047 hours -

r--- measured ....... ....... fL-t-, ---- /TM - ............. I~

...... ...... CC/R ...........

....... '-L, .......

....... 1- ....... r--.. .......... r--.- ....... ....... .. ~- \ .. -----.......

- -~--

60

.01 10 50

Percen I Time

90 99.99

Figure 25. Cumulative distribution of the hourly median data obtained

On the path from KLCS(58) to Point Lorna.

36
50 90 99.99

Percent T,me

10

-----...

, "- "---L

....." . .......

" .... , ....... 1'"1,

, \ ,

' .......

....... .......

KOCEI50l 10 La Mesa ~,

- 3027 hours s:.

measured - ---- ITM ...... CCIR \, I I .......

60

80

.01

20

.

c:: 40

o

....

ClI

;)

c::

Cb

....

....

"'l:

Figure 26. Cumulative distribution of the hourly median data obtained

on the path from KOCE(50) to La Mesa.

o

20

.

c::

0

,

....

'II

;)

c:: 40

Cb

....

....

"'l:

60

--......."I'----- ............ ....... ..... ....... ....... .'. ....... . . .... r-, ' ....... .... ....... ....... "., 1-- .......

-- '"i:; L....,. -- -- ..... - -..------ --- -- "'---L- -- -- -- I --- -- -- KOCEI50l 10 Cowles MIn

3464 hours

measured ---- ITM '-... ...... CCIR

I I

.01 10 50

Percent T,me

90 99.99

Figure 27. Cumulative distribution of the hourly median data obtained

on the path from KOCE(50) to Cowles Mountain.

37
I

,.. I ..

,

"-

" i'" "

"

" \ " " ...

" , \ ,

\ , .... ....

KOCE (50l 10 PI Lorna ...... , l.,

- 4803 hours , ...... "1...

.....

measured - ITM ---- ........ ........ ...... CCIR ' .....

I I

20

c: 40

0

....-

I1J

;)

c:

<b

....

....

't

60

80

.01 10 50

Percent Time

90 99.99

Figure 28. Cumulative distribution of the hourly median data obtained

on the path from KOCE(50) to Point Loma.

20

40

.

c:

0

....-

I1J

;)

c: 60

<b

....

....

't

80

KTSC(8J 10 Boulder

2081 hours

, "- , measured

, ---- ITM

, , ...... CCIR

,

' .... ,

, ........

........

----.. 1"- ....

........

L.....- """"L-- -

IL- ........

r--1--1 ............ L-r--..,. ,~

..... "t , ,

.01 10 50

Percen t Time

90 99.99

Figure 29. Cumulative distribution of the hourly median data obtained

on the path from KTSC(8), Pueblo, to Boulder.

38
Cumulative distributions corresponding to the eight paths from Mount

Wilson are in Figures 18 through 25. It is somewhat surprising that the

extrapolated CCIR method seems fairly accurate for the Channel 7 paths but

ridiculously low for the five UHF paths. The reason the predicted signal

levels are low appears to be the high value used for the terrain irregularity

parameter 6h, and clearly, since the direct ray passes well above most of the

more rugged parts of the terrain, this irregularity should have little to do

with the actual received levels. Indeed, a later version of this method

(CCIR, 1982) has almost removed this parameter from consideration.

One expects a path in southern California to be involved in two or more

propagation modes because there will be times when a strong super-refractive

layer is present and times when it is not; and perhaps there will be times

when such a layer lies above the path and times when it lies below. Each

propagation mode will have its own statistics and the combination into one

cumulative distribution ought to show up as somewhat segmented. Note that

atmospheric layers will sometimes give rise to enhanced fields that should

displace the small percentiles upward, and that also they may introduce radio

holes and suppressed fields and so displace the large percentiles downward.

Mixed mode behavior seems consistent with several of the observed

cumulative distributions. For example, the paths from KOCE (in Figures 26,

27, and 28) have distributions with definitely changing slopes. These are

paths that we have already indicated were probably particularly sensitive to

the presence of layers. The distribution in Figure 23 also seems to involve

different modes of propagation. That in Figure 22, however, appears to be a

pure straight line. But these two paths are physically almost identical,

their only difference being a minor change in frequency. Why their signallevel distribution should be so qualitatively different is a puzzling

question. Our own suspicion is that the answer lies merely in the difference

between the hours of operation of the two stations.

Variability in the southern California paths can often be very large.

The cumulative distributions of hourly medians sometimes have ranges of more

than 70 dB. On the other hand, when we look at the eastern Colorado path in

Figure 29, we find an extremely flat distribution with an interdecile range of

only 6 dB. One probable reason for this is the thin atmosphere in Colorado;

but another reason is perhaps that the odd terrain profile in Figure 15 causes

the path to behave like a knife-edge path. It is known (see, e.g., Barsis and

39
Kirby, 1961) that such paths often exhibit a reduced variability. Of course,

counterexamples also abound: the KOCE to Cowles Mountain path in Figures 13

and 27 is very clearly a knife-edge path but the observed signal-level

distribution is certainly a steep one.

For some of o~r recently acquired data, the present radio propagation

models seem already adequate; for others the differences are large but

explainable. Yet others probably require further study. But to us it seems

the difficult problem, and the problem needing immediate study, is that of

predicting for a given path into which of these simple classifications it will

fall--i.e., whether it will fit present models or will "need explanation."

4. ACKNOWLEDGMENTS

The authors would like to acknowledge the efforts of the many people who

were involved in the measurement program. Victor Tawil of the FCC Office of

Science was the overall manager of the program, and personnel at the FCC Field

Office in San Diego aided in the operations. Anita Longley and Harold

Dougherty, formerly at ITS, were important elements of the original planning

stage. And William Kissick of ITS was project leader to plan, design, and

assemble the automated propagation measurement system. He was assisted by

many others at ITS.

40
5. REFERENCES

Abramowitz, M., and I. A. Stegun (1964), Handbook of Mathematical Functions,

N.B.S. Applied Mathematics Series 55 (U.S. Government Printing Office,

Washington, D.C. 20402). ---

Barsis, A. P., and R. S. Kirby (1961), VHF and UHF signal characteristics

observed on a long knife-edge diffraction path, J. Research NBS 650

(Radio Prop), pp. 437-448. -

CCIR (1978a), Propagation data requi red for trans-horizon radio-rel ay systems

Doc. XIVth Plenary V, Report No. 238-3.

CCIR (1978b), The evaluation of propagation factors in interference problems

at frequencies greater than 0.6 GHz, Doc. XIVth Plenary V, Report No.

569-1.

CCIR (1982), The evaluation of propagation factors in interference problems

between stations on the surface of the Earth and frequencies above about

0.5 GHz, Doc. XVth Plenary V, Report No. 569-2.

Dougherty, H. T. (1968), A survey of microwave fading mechanisms, remedies,

and applications, ESSA Technical Report ERL 69-WPL4 (NTIS Access. No.

COM-71-50288) (see especially p. 42).

Dougherty, H. T., and E. J. Dutton (1981), The role of elevated ducting for

radio service and interference fields, NTIA Report 81-69 (NTIS Access.

No. PB 81-206138).

Hufford, G. A., A. G. Longley, and W. A. Kissick (1982), A guide to the use of

the ITS Irregular Terrain Model in the area prediction mode, NTIA Report

82-100 (NTIS Access. No. PB 82-217977).

Longley, A. G., R. K. Reasoner, and V. L. Fuller (1971), Measured and

predicted long-term distributions of tropospheric transmission loss,

Office of Telecommunications Report TRER 16 (NTIS Access. No. COM-75-

11205) •

Longley, A. G., and P. L. Rice (1968), Prediction of tropospheric radio

transmission loss over irregular terrain--a computer method 1968, ESSA

Tech. Report ERL 79-ITS 67 (NTIS Access. No. AD-676-874).

Misme, P. (1974), Affaiblissement de transmission en propagation gUidee par

conduit atmospherique, Annales des telecommunications 12., pp. 105-114.

Norton, K. A., L. E. Vogler, W. V. Mansfield, and P. J. Short (1955), The

probability distribution of the amplitude of a constant vector plus a

Rayleigh-distributed vector, Proc. IRE 43, pp. 1354-1361.

Rayleigh, Lord (1894), The Theory of Sound, second edition, vol. 1, ch. 2

(republished in 1945 by Dover Publications, New York).

41
Rice, P. L., A. G. Longley, K. A. Norton, and A. P. Barsis (1967),

Transmission loss predictions for tropospheric communication circuits,

NBS Tech. Note 101, Vo1s. I and II. (NTIS Access. Nos. AD-687-820 and

AD-687-821).

Shkarofsky, I.P., and S. B. Nickerson (1982), Computer modeling of mu1tipath

propagation: Review of ray-tracing techniques, Radio Sci. pp. 1133-

1158 (see especially p. 1137).

Weibu11, W. (1951), A statistical distribution function of wide applicability, J. App1. Mech. ~, pp. 293-297.

42
FORM NTIA-29 U.S. DEPARTMENT OF COMMERCE

(4-80) NAT'L TELECOMMUNICATIONS AND INFORMATION ADMINISTRATION

BIBLIOGRAPHIC DATA SHEET

1. PUBLICATION NO. 2. Gov't Accession No. 3. Recipient's Accession No.

NTIA Report 85-177

4. TITLE AND SUBTITLE 5. Publication Date

A Study of Interference Fields in a Ducting Envi I~onment June 1985

6. Performing Organization Code

7. AUTHOR(S) 9. Project/Task/Work Unit No.

Georqe A. Hufforrt and Donald R. EbalJoh Jr.

8. PERFORMING ORGANIZATION NAME AND ADDRESS 9108102

U.S. Department of Commerce

National Telecommunications & Information Admin. 10. Contract/Grant No.

Institute for Telecommunication Sciences

Boulder, Colorado 80303

11. Sponsoring Organization Name and Address 12. Type of Report and Period Covered

13.

14. SUPPLEMENTARY NOTES

15. ABSTRACT (A 200-word or less factual summary of most significant information. If document includes a significant bibliography or literature

survey, mention it here.)

In a cooperative program, the Federal Communications

Commission and the Institute for Telecommunication Sciences have

begun a study of the interference fields that may arise in a

ducting environment. This report gives some preliminary thoughts

on how enhanced sign a1 levels might be modeled and describes a

measurement program that operated in Southern Cal iforni a.

Comparisons are made between some of the first-order statistics of

the data and two of the possible models and show that there sti 11

remains a large gap between our modeling abilities and real ity.

16. Key Words (Alphabetical order, separated by semicolons)

Key words: long-term variability; radio ducts; radio propagation;

short-term variability; UHF; VHF

17. AVAILABILITY STATEMENT 18. Security Class. (This report) 20. Number of pages

UNLIMITED. Unclassified 42

19. Security Class. (This page) 21. Price:

0 FOR OFFICIAL DISTRIBUTION. Unclassified

-:, U. S. GOVERNMENT PRINTING OFFICE: 1985-576-000/20,024 REGION NO.8