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Modelling of Atmospheric Impairments in Stratospheric
Communications
GORAZD KANDUS*, MIHAEL MOHORI*, ERICH LEITGEB+ and TOMA
JAVORNIK**Department of Communication systems, +Institute of
Broadband Communications
*
Joef Stefan Institute,+
Graz University of Technology*Jamova 39, SI-1000 Ljubljana,
+Inffeldgasse 12, 8010 Graz*SLOVENIA, +AUSTRIA
[email protected], [email protected],
[email protected], [email protected]
Abstract: - Stratospheric communication systems operating in the
millimetre frequency bands are subject toatmospheric impairments
caused by rain and scintillation. In this paper we address
propagation channel modelling ofthese atmospheric impairments. In
particular, we present a rain fading and a scintillation fading
channel model forstratospheric communications. Rain fading is
modelled according to the modified DLR segment approach
forgenerating channel attenuation time series taking into
consideration the specifics of stratospheric communicationsystems,
namely the variable elevation angle and different carrier
frequency. Additional fading due to scintillation,which may be
harmful in deep fades caused by the rain, is modelled by adjusting
the satellite scintillation channelmodel so that the amount of
scintillation fading is correlated to the attenuation caused by the
rain. The two modelswere implemented in a software tool enabling
generation of the propagation channel attenuation time series for
thefixed and the mobile stratospheric communication systems.
Key-Words: - rain fading, scintillation fading, millimetre
frequency band, stratospheric communication system,propagation
channel model
1. Introduction
Aerial platforms equipped with suitablecommunications payload
have recently emerged as acomplementary communications
infrastructure tocurrently available terrestrial or satellite
wirelesscommunication systems. They can take a form of anairship or
an airplane, and can be manned or unmanned.These options
importantly influence the mainparameters of the mission including
the duration,altitude, service scenario, and others. Aerial
platformsoperating in lower stratosphere, typically at
altitudesbetween 17 and 22 km, are particularly interesting forthe
provision of communication services and are in the
literature usually referred to as High Altitude Platforms(HAPs)
[1]. There are numerous advantages ofstratospheric communication
systems compared to thesatellite ones. These include easy and low
costlaunching of the platform, low propagation delay,smaller size
of terminal equipment, lower powerconsumption and the possibility
for landing theplatform for maintenance, replacing and upgrading
ofthe equipment. Compared to terrestrial broadbandwireless access
systems, characterised by a harsh multi-path propagation
environment, the propagation channelto/from stratospheric platform
can be most of the timeconsidered as a line of sight (LOS) due to
highelevation angle between the user and a HAP, which
results in less complex terminals achieving higher
datathroughputs. This is particularly true for fixed point-to-point
and point-to-multipoint systems with highly
directional antennas.Depending on communication services
foreseen tobe provided via HAPs the InternationalTelecommunications
Union (ITU) permitted the use ofseveral frequency bands, including
a band at 2 GHz for3G mobile communication services [2] and two
bandsfor broadband services in the millimetre-wavefrequencies,
namely at 47-48 GHz and 28-31 GHz. Inthe millimetre frequency bands
the atmosphericimpairments such as rain attenuation and
scintillationmay cause severe degradation of the systemperformance
even in LOS channel conditions. In order
to design, verify and optimize a communication systema suitable
model of the communication channel isrequired. The deterministic
channel models applyingbasic principles of radio wave propagation
such asreflection, diffraction, scattering, etc., are too
complexand additionally require huge databases on
operatingenvironment with geometrical and electricalcharacteristics
of obstacles. The empirical channelmodels are thus typically a good
compromise betweenthe accuracy and complexity of the model.
However,good channel models are typically based onmeasurement
campaigns carried out over long periods
of time. Of course this is not possible in the case of
anemerging communication system due to non existing
2nd WSEAS Int. Conf. on CIRCUITS, SYSTEMS, SIGNAL and
TELECOMMUNICATIONS (CISST'08)Acapulco, Mexico, January 25-27,
2008
ISSN: 1790-5117Page 86 ISBN: 978-960-6766-34-3
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equipment, i.e. a stable flying stratospheric platform inthis
particular case. As we show in this paper theproblem can be solved
by taking an existing similarchannel model and modifying its
parameters accordingto the specifics of the analyzed communication
system.Thus, we adapt models of rain attenuation andscintillation
of the satellite channels at the millimetrefrequency band to model
the stratosphericcommunication channel.
This paper is organized as follows. At first thechannel models
for rain attenuation and scintillation in ageostationary satellite
system are briefly described.Next, the difference between satellite
propagationchannel and the stratospheric propagation channel
isdiscussed. This is followed by the description of a
newstratospheric channel model for rain attenuation
andscintillation. Finally, the simulation tool developed for
generating channel attenuation time series is describedbefore we
discuss some representative results andconclude with further ideas
to improve the model.
2. Satellite channel models
One of the major problems in the design of the satellitelink
budget operating in millimetre frequency bands isfluctuation of the
amplitude and phase of the receivedsignal due to rain and
scintillation. In the following wedescribe both phenomena and the
approach for theirmodelling.
2.1. Rain fading
Rain fading represents signal attenuation due to
precipi-tations, clouds and other meteorological phenomena,where
the precipitations have the greatest impact. Itsporadically causes
the signal attenuation in satelliteand terrestrial communication
systems operating inmillimetre frequency bands. The impact of rain
fadingon the communication system performance mainlydepends on the
rain rate, type of the rain (showers,heavy rain, drizzle, etc.) and
the thickness of clouds. Its
type can be characterized by the corresponding climatezone as
defined by ITU-R. The ITU-R providesrecommendations concerning the
rain effects on radiowave propagation, but those recommendations
refer toaverage conditions, which are not sufficient in theprocess
of design and analysis of the communicationsystems. Thus, typical
approaches for modelling rainattenuation are based either on
convertingmeteorological data into channel attenuation series oron
setting the parameters of time series attenuationgenerator
according to the measurement resultsobtained by long term
measurement campaigns [3].
In satellite communication systems, two basicapproaches, which
represent a good compromise
between the channel model accuracy and complexity,have been used
to model the rain fading and to generatethe time series of
attenuation: Markov chain approach used in ONERA simulator
[3,4] and DLR segment approach [3,5].
The ONERA Markov channel model [4] consists ofmacroscopic model,
microscopic model and acomponent that combines the outputs of both
models.The macroscopic model is a 2-state Markov chainconsisting of
rain state and clear sky state. It followslong-term behaviour of
rain fading taking into accountthe mean duration of rain events.
The parameters ofmacroscopic models can be derived from the
radiometeorological data banks such as ITU-R or theEuropean Centre
for Medium-Range Weather Forecasts(ECMWF). The ITU-R P.387
Recommendation
provides the probability of the rain averaged over oneyear, from
which all necessary macroscopic parametersof the model can be
calculated. The microscopic modelis an N-state Markov chain which
generates the timeseries with high resolution and gives the
short-termdynamic behaviour of rain attenuation [3].
The DLR segment channel approach is based on aMarkov chain and
Gaussian random variables generator[3,5]. It consists of a generic
part and a specific set ofparameters that allow adjustment of the
channel modelto different elevation angles, carrier frequencies
andclimatic zones. The model specifies three types of
channel attenuation segments: The channel attenuation segment
with almost
constant received power referred to as C-segment. The channel
attenuation segment with mainly
monotonously decreasing channel attenuationreferred to
asD-segment.
The channel attenuation segment with mainlymonotonously
increasing channel attenuationreferred to as U-segment.For each
segment the conditional distribution P(y|x)
is calculated based on a measurement campaign. Theconditional
distribution P(y|x) denotes the likelihoodthat the current channel
attenuation in dB is yconditioned that seconds before the
attenuation hasbeen x. According to satellite channel measurements
itturned out that the is around 1s and P(y|x) obeysGaussian
distribution. The standard deviation and meanvalue of the Gaussian
distribution depends on thesegment (C,U,D), current attenuation and
of course onlatitude, longitude of measurements and
satelliteelevation angle. The switching between channelattenuation
is determined by calculating the differencebetween channel
attenuation in successive time
intervals a(iT)=a(iT)-a((i-1)T) where a(iT) denotes
theattenuation at i-th time interval
2nd WSEAS Int. Conf. on CIRCUITS, SYSTEMS, SIGNAL and
TELECOMMUNICATIONS (CISST'08)Acapulco, Mexico, January 25-27,
2008
ISSN: 1790-5117Page 87 ISBN: 978-960-6766-34-3
