PROJECT SUMMARY REPORT
Improved RF Signal Propagation through Water via
Waveforms
Submitted To
The 2013 Academic Year NSF AY-REU Program
Part of
NSF Type 1 STEP Grant
Sponsored By
The National Science Foundation
Grant ID No.: DUE-0756921
College of Engineering and Applied Science
University of Cincinnati
Cincinnati, Ohio
Prepared By
Justin Jantzen, Senior, Aerospace Engineering
Ritesh Patel, Senior, Electrical/Computer Engineering, ACCEND
Report Reviewed By:
Dr. Dharma Agrawal, D.Sc.
REU Faculty Mentor
Distinguished Professor
School of Computing Sciences & Informatics
University of Cincinnati
January 7 – April 12, 2013
Abstract:
The purpose of this research is to investigate signal propagation radio-frequency
signals through a waveform as compared to propagation simply through the water
medium. Waveforms used will include plastic and copper pipes in order to gain an
understanding of signal attenuation and reflection with the different mediums. Typically,
electromagnetic wave propagation through water is limited in its range by the attenuation
of the signal. Radio-frequency communication through water is superior to the alternatives,
acoustic or optical transmission, because of its high bandwidth and ability to pass the airwater interface easily.
I.
Introduction:
Underwater communications are an important and expanding field of research; not
only do enormous off-shore drilling platforms send pipes down thousands of feet to the
ocean floor, but much of the transatlantic internet communication taking place every day is
accomplished via Atlantic-spanning fiber optic cables. Between the interests of oil
companies and telecommunication companies there is also the interests of marine biology
and ocean floor mapping.
Typically, if any communications are achieved wirelessly in these underwater
applications they are done using acoustic signals. Acoustic signals offer a range up to 20
kilometers and have been used extensively for decades. However, they fall short in their
susceptibility to interference from water turbidity, ambient noise, and their ineffectiveness
as crossing the air-water boundary. This is to say nothing of the low bandwidth offered
from acoustic signals, reaching a maximum of 20 kb/s. An alternative to acoustic signals are
optical signals, offering a high and bandwidth on the order of gigabits per second and low
cost of equipment; however, optical signals likewise have trouble with the air-water
interface, are affected by turbidity, particles, and marine fouling, and are also extremely
limited by range and require line-of-sight. A list of the benefits and limitations of each
method of underwater wireless communication can be seen in Table 1 below.
Table 1: Benefits and Limitations of the Main 3 Methods of Wireless Underwater Communication 1
A promising alternative to the above approaches to underwater communications is
that of radio frequency (RF) signals. RF signals offer a high bandwidth, ability to cross the
air-water boundary, no line-of-sight is required, and there is little interference due to water
turbidity, salinity, etc. The main issue which surfaces when attempting to utilize RF signals
under water is that of strong attenuation of RF signals limiting the range of RF signals,
along with susceptibility to electromagnetic interference.
The purpose of this paper is to determine the efficacy of underwater
communications via RF signals when propagated through a waveform, in this case a pipe,
rather than directly through water. By using air as the propagation medium, water
attenuation can be bypassed in order to take advantage of the bandwidth and range of RF
signals in air. Furthermore, the effect of waveform material and cross-sectional area of the
waveform will be investigated.
II.
Materials and Methods:
The materials used in this project are: one meter of 1-1/2-in diameter, 235 PSI –rated
copper pipe as a waveform; one meter 1-1/2-in diameter, 330 PSI-rated Schedule 40 PVC
pipe as a waveform; one meter 2-in diameter, 330 PSI-rated Schedule 40 PVC pipe as a
waveform; one meter 3-in diameter, 330 PSI-rated Schedule 40 PVC pipe as a waveform;
two Texas Instruments eZ430-RF2500T wireless target boards utilizing CC2500, 2.4 GHz
(2400-2483.5 MHz min/max frequency, assumed 2400 MHz), ISM band multi-channel low
power transceivers; and thin plastic wrap and Duck-brand duct tape were used to insulate
one end of each pipe. In order to submerge the pipes and sensor in water, a 66cm-tall
plastic bin was filled with tap water. The sensor was placed within two sealed Ziploc plastic
bags for insulation from the water for only the tests not involving placing the sensor in a
pipe.
In order to test the signal strength in order to measure signal propagation, the Texas
Instruments eZ430-RF2500 sensor using the eZ430-RF2500-SEH sensor monitor software
v2.5, which comes with the sensors, was used. The attached base station sensor measures
temperature data from a wireless node as well as Received Signal Strength Indicator (RSSI),
recorded as a percentage once every 5 to 6 seconds, depending on signal quality. These
percentages are acceptable as a measurement for this project because the outcome is a
comparison of the average RSSI result recorded for each method--so long as all results are
in a percentage of RSSI, valid comparisons can be made. The RSSI percentages obtained
were then converted into a percent of the maximum signal strength achieved, recorded
when the sensor and the base station were nearly touching with no obstructions between.
This value was 44. Values discussed below are percentages of this value, so a value of 50%
would be half of 44, or 22.
The signal strength was recorded using three methods: the sensor with no waveform (but
insulated in sealed plastic bags), the sensor in a copper waveform, and the sensor in PVC
waveforms of varying diameters. The testing was accomplished by first placing the sensor
in a given insulated pipe outside of water at the same distance from the base station as
when placed in water in order to give a baseline for all three methods. The water-filled bin
was then placed in the same location as previous not-submerged testing and results were
taken with each method submerged in water. As the waveforms were using air as the RF
propagation medium, the pipes were only partially submerged in water, with the unsealed
pipe end open to the air above the surface of the water.
RSSI was recorded for each case at a nominal 5-second interval for either a minute or until
at least 10 data points were recorded. The interval between successful signals received by
the base station varies based on signal strength, with low signal strengths often having
intervals of 30 seconds or more.
III.
Results:
Figure 1: Stacked Histogram of RSSI Percentages of the 3 Methods When Not Submerged in Water
Figure 2: 3-D Histogram of RSSI Percentages of the 3 Methods When Not Submerged in Water
Figure 3: Stacked Histogram of RSSI Percentages of the 3 Methods When Submerged in Water
Figure 4: 3-D Histogram of RSSI Percentages of the 3 Methods When Submerged in Water
Average Percent Signal Received
Plastic
Bags
1.5" Copper
Pipe
1.5" PVC
Pipe
2" PVC
Pipe
3" PVC
Pipe
Not Submerged
59.62
35.68
66.52
65.30
58.31
Not Submerged σ
0.997
2.408
1.040
2.347
2.735
Submerged
32.77
0.00
43.02
40.26
43.01
Submerged σ
1.17
0.00
0.61
2.08
2.54
Table 2: Average RSSI, in Percentage of Maximum RSSI, where σ is Standard Deviation
Not Submerged
Submerged
Plastic
Bags
40.39
67.24
Average Percent Signal Lost
1.5" Copper
1.5" PVC
2" PVC
Pipe
Pipe
Pipe
64.32
33.49
34.70
100.00
56.98
59.74
3" PVC
Pipe
41.69
56.99
Table 3: Average RSSI Lost, compared to Maximum RSSI
IV.
Discussion:
The PVC waveforms performed as expected, as seen in Figure 3 and 4 above, with average
RSSI percentages in water of 43.02%, 40.26%, and 43.01%, from Table 2 above, compared
to that of the sensor only within sealed bags with a mean RSSI percentage of 32.77%, an
increase of 31.3 in mean values using a 1-1/2 in. diameter PVC waveform. All data sets have
little spread (see standard deviations in Table 2, above) and therefore the mean is a good
indicator of a typical value at the given operating condition.
Comparing the average RSSI percentage values for un-submerged tests to the averages
found in the submerged tests, the sensor outside of a waveform saw a decrease of 45% in
the average RSSI percentage, whereas the PVC waveforms saw only a 35%, 38%, and 26%
decrease in the average RSSI percentage when submerged in water.
Interestingly, no signals were able to be recording using the copper pipe waveform when
submerged in water. Figures 1 and 2 show that it had decreased signal propagation
compared to the other two methods even when out of water, but initial research showed
that copper should be an ideal waveform. A possible reason for the poor performance of
the copper pipe could be that the pipe was not insulated externally, causing absorption of
the RF signals. When in water, the attenuation of the water and the absorption of the
copper material could cause a dramatic loss in signal. However, no literature was found
stating the relationship between an insulated and not insulated copper pipe as a waveform.
This is an area in which further testing could be pursued.
The above results show that at the given pipe diameters, length, pipe materials, and RF
frequency PVC is an effective waveform for RF signal propagation as compared to
propagation through water. However, copper at the given specifications does not appear to
be a good waveform in the slightest. Lastly, larger waveform cross-sectional areas have a
small, but negative effect on signal propagation.
Acknowledgements:
Funding for this research was provided by the NSF CEAS AY REU Program, Part of NSF
Type 1 STEP Grant, Grant ID No.: DUE-0756921. We would also like to thank Dr. Dharma
Agrawal and Anagha Jamthe for their help and support with this project.
References
1. Che, X.; Wells, I.; Dickers, G.; Kear, P.; Gong, X., "Re-evaluation of RF electromagnetic
communication in underwater sensor networks," Communications Magazine, IEEE ,
vol.48, no.12, pp.143,151, December 2010
2. Hunt, Kenneth, Niemeier, James, Kruger, Anton. RF communications in underwater
wireless sensor networks. 2010 IEEE International Conference on Electro
Information Technology. 2010.
3. Lloret J. Underwater wireless sensor communications in the 2.4 GHz ISM frequency
band. Sensors (Basel, Switzerland). 2012;12:4237-64.