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dc.contributor.authorPelekanakis, Konstantinos
dc.contributor.authorCazzanti, Luca
dc.date.accessioned2019-06-18T10:07:19Z
dc.date.available2019-06-18T10:07:19Z
dc.date.issued2019/05
dc.identifier.govdocCMRE-PR-2019-025en_US
dc.identifier.urihttp://hdl.handle.net/20.500.12489/766
dc.description.abstractThis paper deals with adaptive underwater acoustic (UWA) communications where the receiver must operate at low signal-to-noise ratios (SNRs). The proposed modem is equipped with a set of direct sequence spread spectrum (DSSS) signals of various coding rates and modulation orders. A channelestimate based decision feedback equalizer (CEB-DFE) is used at the receiver. We address the challenge of achieving high spectral efficiencies subject to a combination of bit-error rate (BER) and SNR constraints. To this end, adaptive selection of signals is achieved based on their BER prediction via boosted trees. This ensemble of trees learns directly from the received data and relates the BER with signal characteristics and channel metrics. The efficiency of the boosted trees is validated by post-processing thousands of acoustic signals recorded in the Gulf of La Spezia, Italy. 10-20 times faster communications as compared to a modem with a fixed rate transmission is achieved.en_US
dc.format6 p. : ill. ; digital, PDF fileen_US
dc.language.isoenen_US
dc.publisherCMREen_US
dc.sourceIn: OCEANS 2018 MTS/IEEE Charleston, 22-25 October 2018, doi: 10.1109/OCEANS.2018.8604521en_US
dc.subjectUnderwater communicationsen_US
dc.subjectAcoustic communicationsen_US
dc.subjectSignal to noise ratio (SNR)en_US
dc.subjectMachine learningen_US
dc.subjectRegression analysisen_US
dc.subjectProbability of interceptionen_US
dc.titleOn adaptive modulation for low SNR underwater acoustic communicationsen_US
dc.typeReprint (PR)en_US
dc.typePapers and Articlesen_US


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