Tones for Real: Managing Multipath in Underwater Acoustic Wakeup. Syed, A. A., Heidemann, J., & Ye, W. ACM Transactions on Sensor Networks, 9(3):27:1–27:24, August, 2013. ![Tones for Real: Managing Multipath in Underwater Acoustic Wakeup [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi 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, with much lower attenuation than RF, but acoustic propagation is five orders-of-magnitude slower than RF, so propagation times stretch to hundreds of milliseconds. Low-power wakeup tones are present in new underwater acoustic modems, and when added to applications and MAC protocols they reduce energy consumption wasted on idle listening. Unfortunately, underwater acoustic tones suffer from \emphself-multipath—echoes unique to the latency that can completely defeat their protocol advantages. We introduce \emphSelf-Reflection Tone Learning (SRTL), a novel approach where nodes use Bayesian techniques to address interference by learning to discriminate self-reflections from noise and independent communication. We present detailed experiments using an acoustic modem in controlled and uncontrolled, in-air and underwater environments. These experiments demonstrate that SRTL's knowledge corresponds to physical-world predictions, that it can cope with underwater noise and reasonable levels of artificial 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.
@Article{Syed13a,
author = "Affan A. Syed and John Heidemann and Wei Ye",
title = "Tones for Real: Managing Multipath in Underwater Acoustic Wakeup",
journal = "ACM Transactions on Sensor Networks",
year = 2013,
sortdate = "2013-08-01",
project = "ilense, ortun, cisoft",
jsubject = "sensornet_high_latency",
volume = 9,
number = 3,
pages = "27:1--27:24",
month = aug,
location = "johnh: pafile",
keywords = "underwater MAC, self-reflection",
url = "http://www.isi.edu/%7ejohnh/PAPERS/Syed13a.html",
pdfurl = "http://www.isi.edu/%7ejohnh/PAPERS/Syed13a.pdf",
doi = "http://dx.doi.org/http://dx.doi.org/10.1145/2422966.2422984",
myorganization = "USC/Information Sciences Institute",
copyrightholder = "ACM",
copyrightterms = " Permission to make digital or hard copies of portions of this work for personal or classroom use is granted without fee provided that the copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page in print or the first screen in digital media. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. otherwise, to republish, to post on servers, or to redistribute to lists, requires prior specific permission and/or a fee. Send written requests for republication to ACM Publications, Copyright & Permissions at the address above or fax +1 (212) 869-0481 or email permissions@acm.org." ,
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, with much lower attenuation than RF, but
acoustic propagation is five orders-of-magnitude slower than RF, so
propagation times stretch to hundreds of milliseconds. Low-power
wakeup tones are present in new underwater acoustic modems, and when
added to applications and MAC protocols they reduce energy consumption
wasted on idle listening. Unfortunately, underwater acoustic tones
suffer from \emph{self-multipath}---echoes unique to the latency that
can completely defeat their protocol advantages. We introduce
\emph{Self-Reflection Tone Learning} (SRTL), a novel approach where
nodes use Bayesian techniques to address interference by learning to
discriminate self-reflections from noise and independent
communication. We present detailed experiments using an acoustic
modem in controlled and uncontrolled, in-air and underwater
environments. These experiments demonstrate that SRTL's knowledge
corresponds to physical-world predictions, that it can cope with
underwater noise and reasonable levels of artificial 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."
,}
Downloads: 0
{"_id":"9HLtChusAXPwPc4H2","bibbaseid":"syed-heidemann-ye-tonesforrealmanagingmultipathinunderwateracousticwakeup-2013","author_short":["Syed, A. A.","Heidemann, J.","Ye, W."],"bibdata":{"bibtype":"article","type":"article","author":[{"firstnames":["Affan","A."],"propositions":[],"lastnames":["Syed"],"suffixes":[]},{"firstnames":["John"],"propositions":[],"lastnames":["Heidemann"],"suffixes":[]},{"firstnames":["Wei"],"propositions":[],"lastnames":["Ye"],"suffixes":[]}],"title":"Tones for Real: Managing Multipath in Underwater Acoustic Wakeup","journal":"ACM Transactions on Sensor Networks","year":"2013","sortdate":"2013-08-01","project":"ilense, ortun, cisoft","jsubject":"sensornet_high_latency","volume":"9","number":"3","pages":"27:1–27:24","month":"August","location":"johnh: pafile","keywords":"underwater MAC, self-reflection","url":"http://www.isi.edu/%7ejohnh/PAPERS/Syed13a.html","pdfurl":"http://www.isi.edu/%7ejohnh/PAPERS/Syed13a.pdf","doi":"http://dx.doi.org/http://dx.doi.org/10.1145/2422966.2422984","myorganization":"USC/Information Sciences Institute","copyrightholder":"ACM","copyrightterms":"Permission to make digital or hard copies of portions of this work for personal or classroom use is granted without fee provided that the copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page in print or the first screen in digital media. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. otherwise, to republish, to post on servers, or to redistribute to lists, requires prior specific permission and/or a fee. Send written requests for republication to ACM Publications, Copyright & Permissions at the address above or fax +1 (212) 869-0481 or email permissions@acm.org.","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, with much lower attenuation than RF, but acoustic propagation is five orders-of-magnitude slower than RF, so propagation times stretch to hundreds of milliseconds. Low-power wakeup tones are present in new underwater acoustic modems, and when added to applications and MAC protocols they reduce energy consumption wasted on idle listening. Unfortunately, underwater acoustic tones suffer from \\emphself-multipath—echoes unique to the latency that can completely defeat their protocol advantages. We introduce \\emphSelf-Reflection Tone Learning (SRTL), a novel approach where nodes use Bayesian techniques to address interference by learning to discriminate self-reflections from noise and independent communication. We present detailed experiments using an acoustic modem in controlled and uncontrolled, in-air and underwater environments. These experiments demonstrate that SRTL's knowledge corresponds to physical-world predictions, that it can cope with underwater noise and reasonable levels of artificial 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":"@Article{Syed13a,\n\tauthor = \t\"Affan A. Syed and John Heidemann and Wei Ye\",\n\ttitle = \t\"Tones for Real: Managing Multipath in Underwater Acoustic Wakeup\",\n\tjournal = \t\"ACM Transactions on Sensor Networks\",\n\tyear = \t\t2013,\n\tsortdate = \"2013-08-01\",\n\tproject = \"ilense, ortun, cisoft\",\n\tjsubject = \"sensornet_high_latency\",\n\tvolume = \t9,\n\tnumber = \t3,\n\tpages = \t\"27:1--27:24\",\n\tmonth = \taug,\n\tlocation = \t\"johnh: pafile\",\n\tkeywords = \t\"underwater MAC, self-reflection\",\n\turl = \"http://www.isi.edu/%7ejohnh/PAPERS/Syed13a.html\",\n\tpdfurl = \"http://www.isi.edu/%7ejohnh/PAPERS/Syed13a.pdf\",\n\tdoi = \"http://dx.doi.org/http://dx.doi.org/10.1145/2422966.2422984\",\n\tmyorganization =\t\"USC/Information Sciences Institute\",\n\tcopyrightholder = \"ACM\",\n\tcopyrightterms = \"\tPermission to make digital or hard \tcopies of portions of this work for personal or \tclassroom use is granted without fee provided that \tthe copies are not made or distributed for profit or \tcommercial advantage and that copies bear this \tnotice and the full citation on the first page in \tprint or the first screen in digital \tmedia. Copyrights for components of this work owned \tby others than ACM must be honored. Abstracting with \tcredit is permitted. \totherwise, to republish, to post on servers, or to \tredistribute to lists, requires prior specific \tpermission and/or a fee. Send written requests for \trepublication to ACM Publications, Copyright & \tPermissions at the address above or fax +1 (212) \t869-0481 or email permissions@acm.org.\" ,\n\tabstract = \"The principles of sensor networks---low-power, wireless, in-situ\nsensing with many inexpensive sensors---are only recently penetrating\ninto underwater research. Acoustic communication is best suited for\nunderwater communication, with much lower attenuation than RF, but\nacoustic propagation is five orders-of-magnitude slower than RF, so\npropagation times stretch to hundreds of milliseconds. Low-power\nwakeup tones are present in new underwater acoustic modems, and when\nadded to applications and MAC protocols they reduce energy consumption\nwasted on idle listening. Unfortunately, underwater acoustic tones\nsuffer from \\emph{self-multipath}---echoes unique to the latency that\ncan completely defeat their protocol advantages. We introduce\n\\emph{Self-Reflection Tone Learning} (SRTL), a novel approach where\nnodes use Bayesian techniques to address interference by learning to\ndiscriminate self-reflections from noise and independent\ncommunication. We present detailed experiments using an acoustic\nmodem in controlled and uncontrolled, in-air and underwater\nenvironments. These experiments demonstrate that SRTL's knowledge\ncorresponds to physical-world predictions, that it can cope with\nunderwater noise and reasonable levels of artificial noise, and that\nit can track a changing multi-path environment. Simulations confirm\nthat these real-world experiments generalize over a wide range of\nconditions.\"\n,}\n\n","author_short":["Syed, A. A.","Heidemann, J.","Ye, W."],"bibbaseid":"syed-heidemann-ye-tonesforrealmanagingmultipathinunderwateracousticwakeup-2013","role":"author","urls":{"Paper":"http://www.isi.edu/%7ejohnh/PAPERS/Syed13a.html"},"keyword":["underwater MAC","self-reflection"],"metadata":{"authorlinks":{}}},"bibtype":"article","biburl":"https://bibbase.org/f/dHevizJoWEhWowz8q/johnh-2023-2.bib","dataSources":["YLyu3mj3xsBeoqiHK","fLZcDgNSoSuatv6aX","fxEParwu2ZfurScPY","7nuQvtHTqKrLmgu99"],"keywords":["underwater mac","self-reflection"],"search_terms":["tones","real","managing","multipath","underwater","acoustic","wakeup","syed","heidemann","ye"],"title":"Tones for Real: Managing Multipath in Underwater Acoustic Wakeup","year":2013}