Cyclostationarity of Communication Signals in Underwater Acoustic Channels
The effect of underwater acoustic propagation on the cyclostationary features of communication signals is modeled and analyzed. Two kinds of channels are considered: the multiscale-multilag channel, over which mobile and wideband acoustic systems usually communicate, and the dispersive channel resul...
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description | The effect of underwater acoustic propagation on the cyclostationary features of communication signals is modeled and analyzed. Two kinds of channels are considered: the multiscale-multilag channel, over which mobile and wideband acoustic systems usually communicate, and the dispersive channel resulting from low-frequency modal propagation in shallow water. It is shown that multiscale-multilag channels transform cyclostationary signals into a sum of velocity and acceleration-dependent time-warped cyclostationary processes. This time-warping is carefully taken into account to efficiently recover the cyclostationary features. On the other hand, it is found that low-frequency dispersive channels preserve the original periodicity but attenuate the shorter cycles and spread the correlations. To illustrate the theoretical results, applications with simulated and real data are also presented. Specifically, the problem of estimating time-varying Doppler scales is addressed for multiscale-multilag channels as well as the detection of signals with unique cyclostationary signatures. The example of blind symbol-rate estimation applied to covert communications in dispersive channels is also discussed. Special attention is paid to phase-shift keying (PSK), quadrature amplitude modulation (QAM), orthogonal frequency-division multiplexing (OFDM), and direct-sequence spread-spectrum (DSSS) signals. Accompanying supplementary material provides the MATLAB code used for the estimation and detection examples. |
doi_str_mv | 10.1109/JOE.2022.3218106 |
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Two kinds of channels are considered: the multiscale-multilag channel, over which mobile and wideband acoustic systems usually communicate, and the dispersive channel resulting from low-frequency modal propagation in shallow water. It is shown that multiscale-multilag channels transform cyclostationary signals into a sum of velocity and acceleration-dependent time-warped cyclostationary processes. This time-warping is carefully taken into account to efficiently recover the cyclostationary features. On the other hand, it is found that low-frequency dispersive channels preserve the original periodicity but attenuate the shorter cycles and spread the correlations. To illustrate the theoretical results, applications with simulated and real data are also presented. Specifically, the problem of estimating time-varying Doppler scales is addressed for multiscale-multilag channels as well as the detection of signals with unique cyclostationary signatures. The example of blind symbol-rate estimation applied to covert communications in dispersive channels is also discussed. Special attention is paid to phase-shift keying (PSK), quadrature amplitude modulation (QAM), orthogonal frequency-division multiplexing (OFDM), and direct-sequence spread-spectrum (DSSS) signals. 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Two kinds of channels are considered: the multiscale-multilag channel, over which mobile and wideband acoustic systems usually communicate, and the dispersive channel resulting from low-frequency modal propagation in shallow water. It is shown that multiscale-multilag channels transform cyclostationary signals into a sum of velocity and acceleration-dependent time-warped cyclostationary processes. This time-warping is carefully taken into account to efficiently recover the cyclostationary features. On the other hand, it is found that low-frequency dispersive channels preserve the original periodicity but attenuate the shorter cycles and spread the correlations. To illustrate the theoretical results, applications with simulated and real data are also presented. Specifically, the problem of estimating time-varying Doppler scales is addressed for multiscale-multilag channels as well as the detection of signals with unique cyclostationary signatures. The example of blind symbol-rate estimation applied to covert communications in dispersive channels is also discussed. Special attention is paid to phase-shift keying (PSK), quadrature amplitude modulation (QAM), orthogonal frequency-division multiplexing (OFDM), and direct-sequence spread-spectrum (DSSS) signals. Accompanying supplementary material provides the MATLAB code used for the estimation and detection examples.</description><subject>Acoustic communications</subject><subject>Acoustics</subject><subject>Autocorrelation</subject><subject>Channel estimation</subject><subject>cyclostationarity (CS)</subject><subject>Dispersion</subject><subject>Doppler effect</subject><subject>Engineering Sciences</subject><subject>Estimation</subject><subject>modal dispersion</subject><subject>multiscale-multilag channel</subject><subject>Phase shift keying</subject><subject>Signal and Image processing</subject><subject>Spread spectrum communication</subject><subject>underwater warfare</subject><issn>0364-9059</issn><issn>1558-1691</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2025</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNo9kE1LAzEQhoMoWKt3wctePWydSfYrx7LU1lLoQXsOaXbWRra7kmyV_nuztvQ08PK8w8zD2CPCBBHky3I9m3DgfCI4FgjZFRthmhYxZhKv2QhElsQSUnnL7rz_AsAkyeWILcujaTrf6952rXa2P0ZdHZXdfn9orflPo3f72erGR7aNNm1F7lf35KKp6Q6-tyYqd7ptqfH37KYOGD2c55htXmcf5SJeredv5XQVGy55H1coUJKuhDCcwkWVqBF4SFJDOQnIpEAQsC0o5UiUprkJH-W45YmWmKAYs-fT3p1u1Leze-2OqtNWLaYrNWSQYNibFz8DCyfWuM57R_WlgKAGbyp4U4M3dfYWKk-niiWiCy6lLII98QctOmhe</recordid><startdate>2025</startdate><enddate>2025</enddate><creator>Socheleau, Francois-Xavier</creator><general>IEEE</general><general>Institute of Electrical and Electronics Engineers</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>1XC</scope><scope>VOOES</scope><orcidid>https://orcid.org/0000-0003-0974-5191</orcidid></search><sort><creationdate>2025</creationdate><title>Cyclostationarity of Communication Signals in Underwater Acoustic Channels</title><author>Socheleau, Francois-Xavier</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c292t-d1319ead33c2e905d3f1029ea5ce7e306931030b8e521ee557c21871b24a91413</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2025</creationdate><topic>Acoustic communications</topic><topic>Acoustics</topic><topic>Autocorrelation</topic><topic>Channel estimation</topic><topic>cyclostationarity (CS)</topic><topic>Dispersion</topic><topic>Doppler effect</topic><topic>Engineering Sciences</topic><topic>Estimation</topic><topic>modal dispersion</topic><topic>multiscale-multilag channel</topic><topic>Phase shift keying</topic><topic>Signal and Image processing</topic><topic>Spread spectrum communication</topic><topic>underwater warfare</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Socheleau, Francois-Xavier</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>CrossRef</collection><collection>Hyper Article en Ligne (HAL)</collection><collection>Hyper Article en Ligne (HAL) (Open Access)</collection><jtitle>IEEE journal of oceanic engineering</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Socheleau, Francois-Xavier</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Cyclostationarity of Communication Signals in Underwater Acoustic Channels</atitle><jtitle>IEEE journal of oceanic engineering</jtitle><stitle>JOE</stitle><date>2025</date><risdate>2025</risdate><spage>1</spage><epage>23</epage><pages>1-23</pages><issn>0364-9059</issn><eissn>1558-1691</eissn><coden>IJOEDY</coden><abstract>The effect of underwater acoustic propagation on the cyclostationary features of communication signals is modeled and analyzed. Two kinds of channels are considered: the multiscale-multilag channel, over which mobile and wideband acoustic systems usually communicate, and the dispersive channel resulting from low-frequency modal propagation in shallow water. It is shown that multiscale-multilag channels transform cyclostationary signals into a sum of velocity and acceleration-dependent time-warped cyclostationary processes. This time-warping is carefully taken into account to efficiently recover the cyclostationary features. On the other hand, it is found that low-frequency dispersive channels preserve the original periodicity but attenuate the shorter cycles and spread the correlations. To illustrate the theoretical results, applications with simulated and real data are also presented. Specifically, the problem of estimating time-varying Doppler scales is addressed for multiscale-multilag channels as well as the detection of signals with unique cyclostationary signatures. The example of blind symbol-rate estimation applied to covert communications in dispersive channels is also discussed. Special attention is paid to phase-shift keying (PSK), quadrature amplitude modulation (QAM), orthogonal frequency-division multiplexing (OFDM), and direct-sequence spread-spectrum (DSSS) signals. Accompanying supplementary material provides the MATLAB code used for the estimation and detection examples.</abstract><pub>IEEE</pub><doi>10.1109/JOE.2022.3218106</doi><tpages>23</tpages><orcidid>https://orcid.org/0000-0003-0974-5191</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Acoustic communications Acoustics Autocorrelation Channel estimation cyclostationarity (CS) Dispersion Doppler effect Engineering Sciences Estimation modal dispersion multiscale-multilag channel Phase shift keying Signal and Image processing Spread spectrum communication underwater warfare |
title | Cyclostationarity of Communication Signals in Underwater Acoustic Channels |
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