Tones for Real: Managing Multipath in Underwater Acoustic Wakeup. Syed, A. A. & Heidemann, J. Technical Report ISI-TR-2009-659, USC/Information Sciences Institute, April, 2009. ![Tones for Real: Managing Multipath in Underwater Acoustic Wakeup [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper abstract bibtex The principles of sensor networks—low-power, wireless, in-situ sensing with many inexpensive sensors—are only recently penetrating into underwater research. Acoustic communication is best suited for underwater communication, since other methods (optical and radio) attenuate very quickly. Yet acoustic propagation is five orders-of-magnitude slower than RF, so propagation times stretch to hundreds of milliseconds. A new generation of underwater acoustic modems have added low-power wakeup tones that combat the energy consumption acoustic modems would waste on idle listening. Recently, these tones have been used as an integral part of application layer and MAC protocols. While all wireless data-networks suffer from multipath interference of received data, in this paper, we show that due to large acoustic propagation delay tone echoes cause a unique interference, tone \emphself-multipath, for tone-based protocols. To address this interference we introduce \emphSelf-Reflection Tone Learning (SRTL), a novel approach where nodes use Bayesian techniques to discriminate self-reflections from noise and communication from other nodes. We present detailed experiments using an acoustic modem in two physical environments to show that SRTL's knowledge corresponds to physical-world predictions, that it can cope with reasonable levels of noise, and that it can track a changing multi-path environment. Simulations confirm that these real-world experiments generalize over a wide range of conditions.
@TechReport{Syed09b,
author = "Affan A. Syed and John Heidemann",
title = "Tones for Real: Managing Multipath in Underwater Acoustic Wakeup",
institution = "USC/Information Sciences Institute",
year = 2009,
sortdate = "2009-04-01",
project = "ilense, snuse, ortun, cisoft",
jsubject = "sensornet_high_latency",
number = "ISI-TR-2009-659",
month = apr,
location = "johnh: pafile",
keywords = "underwater MAC, self-reflection",
myorganization = "USC/Information Sciences Institute",
copyrightholder = "authors",
url = "http://www.isi.edu/%7ejohnh/PAPERS/Syed09b.html",
pdfurl = "http://www.isi.edu/%7ejohnh/PAPERS/Syed09b.pdf",
abstract = "The principles of sensor networks---low-power,
wireless, in-situ
sensing with many inexpensive sensors---are only recently penetrating
into underwater research. Acoustic communication is best suited for
underwater communication, since other methods (optical and radio)
attenuate very quickly. Yet acoustic propagation is five
orders-of-magnitude slower than RF, so propagation times stretch to
hundreds of milliseconds. A new generation of underwater acoustic
modems have added low-power wakeup tones that combat the energy
consumption acoustic modems would waste on idle listening. Recently,
these tones have been used as an integral part of application layer
and MAC protocols. While all wireless data-networks suffer from
multipath interference of received data, in this paper, we show that
due to large acoustic propagation delay tone echoes cause a unique
interference, tone \emph{self-multipath}, for tone-based protocols.
To address this interference we introduce \emph{Self-Reflection Tone
Learning} (SRTL), a novel approach where nodes use Bayesian techniques
to discriminate self-reflections from noise and communication from
other nodes. We present detailed experiments using an acoustic modem
in two physical environments to show that SRTL's knowledge corresponds
to physical-world predictions, that it can cope with reasonable levels
of noise, and that it can track a changing multi-path environment.
Simulations confirm that these real-world experiments generalize over
a wide range of conditions.",
}
% title = "Contention Analysis of {MAC} Protocols that Count",
Downloads: 0
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A.","Heidemann, J."],"bibdata":{"bibtype":"techreport","type":"techreport","author":[{"firstnames":["Affan","A."],"propositions":[],"lastnames":["Syed"],"suffixes":[]},{"firstnames":["John"],"propositions":[],"lastnames":["Heidemann"],"suffixes":[]}],"title":"Tones for Real: Managing Multipath in Underwater Acoustic Wakeup","institution":"USC/Information Sciences Institute","year":"2009","sortdate":"2009-04-01","project":"ilense, snuse, ortun, cisoft","jsubject":"sensornet_high_latency","number":"ISI-TR-2009-659","month":"April","location":"johnh: pafile","keywords":"underwater MAC, self-reflection","myorganization":"USC/Information Sciences Institute","copyrightholder":"authors","url":"http://www.isi.edu/%7ejohnh/PAPERS/Syed09b.html","pdfurl":"http://www.isi.edu/%7ejohnh/PAPERS/Syed09b.pdf","abstract":"The principles of sensor networks—low-power, wireless, in-situ sensing with many inexpensive sensors—are only recently penetrating into underwater research. 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We present detailed experiments using an acoustic modem in two physical environments to show that SRTL's knowledge corresponds to physical-world predictions, that it can cope with reasonable levels of noise, and that it can track a changing multi-path environment. Simulations confirm that these real-world experiments generalize over a wide range of conditions.","bibtex":"@TechReport{Syed09b,\n\tauthor = \t\"Affan A. 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Yet acoustic propagation is five\norders-of-magnitude slower than RF, so propagation times stretch to\nhundreds of milliseconds. A new generation of underwater acoustic\nmodems have added low-power wakeup tones that combat the energy\nconsumption acoustic modems would waste on idle listening. Recently,\nthese tones have been used as an integral part of application layer\nand MAC protocols. While all wireless data-networks suffer from\nmultipath interference of received data, in this paper, we show that\ndue to large acoustic propagation delay tone echoes cause a unique\ninterference, tone \\emph{self-multipath}, for tone-based protocols.\nTo address this interference we introduce \\emph{Self-Reflection Tone\nLearning} (SRTL), a novel approach where nodes use Bayesian techniques\nto discriminate self-reflections from noise and communication from\nother nodes. 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