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Space Station External Wireless Communication
System RF Coverage and Link Performance Analysis
Shian U. Hwu, Nathan J. Champagne,
Matthew J. Upanavage, Kanishka deSilva,
Communication System Analysis
JETS, Jacobs Technology
Houston, Texas
Chatwin Lansdowne, Michael A. Khayat,
Haley C. Boose
EV8, Avionics System Division
NASA Johnson Space Center
Houston, Texas
Abstract—A simulation method used to analyze the spacecraft
wireless communication system RF coverage and link
performance is presented in this paper. The method is rigorous,
but practical, and is applied in the Space Station wireless system
performance analysis. Comprehensive numerical results are
presented and discussed. The multipath mitigation techniques
are also presented for the Space Station External Wireless
Communication System applications.
Keywords—wireless; multipath; space station; method of
moments; geometrical theory of diffraction; communications;
avionics; computer simulations
I. INTRODUCTION
Since the completion of the International Space Station
(ISS), NASA’s ISS-related efforts have shifted from
construction missions to scientific payloads and experiment
integration. Since the year 2000, astronauts from partner
nations have been conducting experiments in biology, physics,
astronomy and other science and technology fields on the ISS.
Many research payloads and experiments will be deployed
outside of the ISS modules and remain in space. The ISS
External Wireless Communications (EWC) system provides
high data rate communications between the external scientific
payloads and the internal Ethernet network aboard the ISS.
Both payload developers and NASA will utilize a widely
available and reliable communication protocol (IEEE 802.11)
that requires little to no crew interaction after deployment of
the scientific experiment payloads.
Wireless system radio frequency (RF) coverage analysis is
important for ISS to support the space science and technology
research payloads and associated mission planning and
operations. The wireless communication system performance is
affected by the on-orbit operational environment. The ISS is a
very large and metallic space vehicle that may cause multiple
RF signal reflections that change the signal distribution around
the wireless transmitters. Hence, the signal strength may be
modified due to the constructive and destructive interference
among direct and reflected RF signal components.
Antenna anechoic chamber measurements and/or
electromagnetic simulation tools may be used for RF coverage
analysis. Measuring ISS antenna performance in an anechoic
chamber may be a complicated and expensive task. In some
operational scenarios, ground measurements may be intractable
due to the size of the vehicle influencing the RF coverage. For
this reason, simulation tools are important as a complementary
method for the on-orbit wireless communication coverage and
performance analysis.
A simulation method used to analyze the spacecraft
wireless communication system RF coverage and link
performance is discussed in this paper. The method is rigorous
and practical as applied to the ISS wireless system performance
analysis.
Figure 1. International Space Station.
II. COMPUTER MODELING TECHNIQUES
A rigorous full-wave modeling technique, the Method of
Moments (MoM), may be applied to analyze the antenna
performance, including the near-field effects from the antenna
mounting bracket and other near structures [1,2]. The full
antenna patterns computed from the full-wave modeling
method are then used as the equivalent antenna sources by the
asymptotic modeling technique, the Uniform Geometrical
Theory of Diffraction (UTD). The UTD method is capable of
modeling the multipath effects from the ISS with moderate
computing time and resources [3-7]. This hybrid modeling
approach is capable of including the signal interactions with
the ISS in both the near field and far field.
The RF coverage analysis for the communication
performance requires computing or measuring the intensity of
the signal in a region around the wireless transmitters. The
coverage area for the analysis is determined by comparing the
signal intensity against the required minimum threshold signal
U.S. Government work not protected by U.S. copyright
level based on the data rate and the sensitivity of the radio
receiver.
To compute the signal strength in a selected region, the
electric and magnetic fields of the antenna radiating element
are calculated at receiver grid points and a vector summation is
performed. The total electric signal densities at grid points are
computed from the vector summation of the direct, reflected,
and diffracted signals. Two- and three-dimensional signal
density maps are generated for review.
Computer simulations yield a map of the RF signal strength
in selected areas. The RF coverage is assessed by comparing
the computed signal strength to the required wireless radio
signal sensitivity specifications. Assessing the wireless
coverage area leads to the appropriate operational scenarios to
ensure mission success.
III. NUMERICAL RESULTS
In this section, sample results generated using the proposed
modeling techniques for the ISS applications [8-14] are
presented. The computed antenna gain and axial ratio patterns,
including the mounting bracket effects based on the rigorous
full-wave modeling, are shown in Figures 2 and 3. Note that
both the gain and axial ratio patterns have to be optimized to
achieve the optimum link performance. The antenna gain
should be directed to the region where the coverage is desired.
The axial ratio should be minimized to reduce the polarization
loss and to achieve a better link margin. It turns out that the
axial ratio patterns are sensitive to the antenna mounting
bracket design, so the geometry had to be modeled with care.
Figure 2. The antenna gain pattern computed using full-wave
modeling.
The sample EWC antenna locations for the airlock are shown
in Figure 4. The antenna pattern for each antenna is different
due to the antenna orientation and effect of the airlock
curvature. The ray tracing for the berthed EWC airlock
antennas is shown in Figure 5. It shows the signals travel from
the transmitter to the receiver via multiple propagation paths.
Figure 3. The antenna axial ratio pattern computed using full-
wave modeling.
Figure 4. Proposed EWC antenna locations for the berthed
airlock.
Figure 5. Sample ray tracing for the EWC airlock antennas.
Figure 6. Computer simulations yielded a map of the RF
signal strength in the selected areas of a specified horizontal
plane.
Figure 7. Computer simulations yielded a map of the RF
signal strength in the selected areas of a specified vertical
plane.
Figure 8. Sample ray tracing for the deployed EWC airlock
antennas.
Figure 9. Computer simulations yielded a map of the RF
signal strength in the selected areas of a sample horizontal
plane.
Figure 10. Computer simulations yielded a map of the RF
signal strength in the selected areas of a sample vertical plane.
IV. MULTIPATH FADING MITIGATIONS
The ISS EWC system is operated in a multipath environment,
i.e. where reflections are present and signals arrive at the
receiver from the transmitter by multiple propagation paths.
The total received signal is the sum of all the signals arriving at
the receiver. The multipath signals may be in phase with the
direct signal. This will increase the received signal strength.
The multipath signals may also be out of phase with the direct
signal. This will decrease the received signal strength.
Additionally, signal components from the transmitter will
arrive at the receiver at different times, since they will be
traveling along multiple propagation paths.
The mathematical model of the multipath may be presented
using the complex impulse response, as shown in Figure 11.
The received signal with multipath can be expressed as
į(t-
ɒ
n
)
where N is the number of multipath signal components,
represents the complex amplitude (i.e., magnitude and phase)
of the n
th
multipath component, and
ɒ
n
is the time delay of the
n
th
multipath component relative to the direct signal.
Figure 11. Mathematical model of the multipath impulse
response.
If we change the relative propagation path lengths, this could
be done by moving either the transmitter or receiver antenna
locations. This will result in the different relative phases of the
signals arriving at the receiver, and, in turn, will result in the
different received signal strengths. In a weak signal area,
communication dropouts may occur due to destructive
multipath effects. If we have multiple antennas placed at
different locations, the signals will take different paths to reach
the different antennas. The different paths will have signal
fades that occur in different places. The probability to have a
signal dropout is very low with a Multiple Input Multiple
Output (MIMO) system with multiple antennas separated
spatially, as shown in Figure 12.
Figure 12. The Multiple Input Multiple Output (MIMO)
system with multiple antennas separated spatially.
Antenna Spatial Diversity
The ISS EWC system is a MIMO capable system. Placing
multiple antennas at different locations allows the radio
receiver to determine which signal is best to use. This is
referred to as antenna diversity and is one way to reduce
multipath problems. Antenna Spatial Diversity is an effective
technique, as shown in Figure 13, for a two-antenna diversity
system.
The signal strengths associated with the multiple antennas are
generally not correlated in time or space. When one signal is
near a minimum, the other may be near a maximum. The
selection of one antenna over the others is based on signal
quality.
Figure 13. The signal peaks and nulls are shifted at spatially
separated antennas placed at different locations.
The RF signal strengths in a selected vertical plane based on a
single antenna configuration are shown in Figure 14. By
comparison, the RF signal strengths for the same vertical
plane based on a multiple antenna system with a two-antenna
configuration are shown in Figure 15. A simple best signal
selection from the two spatially separated antennas is
performed. The improvement in the signal strengths and
coverage area are quite noticeable. The advantages of a
MIMO system operated in a multipath environment are
illustrated. A MIMO receiver can exploit the stronger signal
propagation path at any time among the spatially diversified
antennas and, thus, will experience a lower amount of
dropouts.
Figure 14. The RF signal strength in a selected vertical plane
based on single antenna configuration.
Figure 15. The RF signal strength in a selected vertical plane
with two spatially separated antennas.
Subcarrier Frequency Diversity
The EWC system is a multichannel/multi-subcarrier system
which divides the total available channel bandwidth into many
equally spaced subchannels or subcarriers of smaller
bandwidths as shown in Figure 16. A subcarrier carrying a
portion of the data is transmitted in each subchannel. In a
single carrier system, a severe fade or interference can cause
the signal to dropout. In a multi-subcarrier system, only a
portion of the subcarriers will be affected but not the entire
link.
The multipath fade is a frequency dependent phenomenon.
In a multipath environment, there are many rays to reach the
receiver. Therefore, the impulse response of the channel is a set
of delta functions with different amplitude and time delays
depending on each propagation path. The received power on
each path is different. This leads to a non-flat fading frequency
response of the channel bandwidth.
Figure 16. The EWC is a multichannel/multi-subcarrier
system.
The signal reflections in the multipath environment cause the
non-uniform signal power distributions over the bandwidth
where the fading distortion may occur on portion of the total
bandwidth, as shown in Figure 17.
Figure 17. The fading distortion occurs on portion of the total
bandwidth.
The multipath could degrade signals at some subcarrier
frequencies. The signal fades could cause data dropouts for the
affected sub-channels but not all the sub-channels. The impact
of the signal fading due to multipath thus can be reduced by
using a wideband channel receiver with multiple sub-channels.
To illustrate that the multipath fade is a frequency dependent
phenomenon, a simple simulation test with a flat plate
reflection over the Wi-Fi band width is performed (see
Figure 18). The transmitter is placed 1 meter above a flat
reflecting surface. The receiver is moved along a 6-meter
straight line at 1 meter above the reflecting surface. The
received powers were computed at the subcarrier frequencies
of 5.3, 5.55, and 5.8 GHz.
The received powers along the receiver path are shown in
Figure 19. The signal reflections off the flat surface cause both
in-phase and out of phase interference to the direct signals
from the transmitter. As a result, signal peaks and nulls are
observed along the receiver path. However, the signal peaks
and nulls are shifted for different subcarrier frequencies. This
illustrates that the multipath fade is frequency dependent and
could affect some sub-channels but may not cause dropouts
across all the subchannels.
Figure 18. The ray tracing between a transmitter (yellow box)
and multiple receivers (red boxes) along a straight line
receiving path with reflections off a flat ground plate.
-100
-90
-80
-70
-60
-50
-40
-9 -8 -7 -6 -5 -4 -3
Relative Power (dB)
X-Axis (meters)
Frequency Divisity
5.3 GHz 5.55 GHz 5.8 GHz
Figure 19. The received power along a 6-meter receiver route
at three different subchannel frequencies.
V. CONCLUSION
A simulation method to analyze the spacecraft wireless
communication system RF coverage and link performance has
been presented. The method is rigorous but is also practical. It
has been applied to the ISS wireless system RF coverage and
link performance analysis. Comprehensive numerical results
have been presented and discussed. Also, multipath mitigation
techniques for ISS EWC system applications have been
presented.
ACKNOWLEDGMENTS
The authors would like to thank Cathy A. Dempsey of NASA
and Brock Howe of NanoRacks for many helpful data and
technical discussions. The authors also acknowledge the
NASA for the funding to support this work.
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