Exploiting Sparsity for Underwater Acoustic Sensor Network Under Time-Varying Channels
As a time-frequency doubly selective channel, severe multipath, Doppler, as well as the large time-delay characteristics of the underwater acoustic (UWA) channel pose significant challenge to the research and design of UWA communication and network systems. To mitigate these negative factors, inhere...
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Veröffentlicht in: | IEEE internet of things journal 2022-02, Vol.9 (4), p.2859-2869 |
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description | As a time-frequency doubly selective channel, severe multipath, Doppler, as well as the large time-delay characteristics of the underwater acoustic (UWA) channel pose significant challenge to the research and design of UWA communication and network systems. To mitigate these negative factors, inherent sparsity contained in the UWA channel has been extensively investigated to improve UWA communication via a sparsity exploitation receiver. While the performance of the UWA sensor network is highly dependent on that of the physical layer, there are few investigations reported on exploiting channel sparsity from the viewpoint of UWA networking. In this article, a UWA sensor network adopting the sparsity exploitation physical layer is evaluated based on the network simulator 3 (NS-3) simulation tool. The simulation time-varying channel is generated by incorporating the Bellhop channel model with the statistical characteristics extracted from experimental shallow water channels. Three types of physical layers, i.e., those do not adopt sparse exploitation, adopting compressed sensing (CS), as well as the dynamic CS (DCS) technique, are employed for evaluation and comparison of network behavior under different media access control (MAC) protocols. The evaluation results verify the effectiveness of sparsity exploitation in improving UWA sensor network performance in the presence of time variations, while giving a quantitative comparison between enhancement achieved by the CS and DCS sparsity exploitation. |
doi_str_mv | 10.1109/JIOT.2021.3094818 |
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To mitigate these negative factors, inherent sparsity contained in the UWA channel has been extensively investigated to improve UWA communication via a sparsity exploitation receiver. While the performance of the UWA sensor network is highly dependent on that of the physical layer, there are few investigations reported on exploiting channel sparsity from the viewpoint of UWA networking. In this article, a UWA sensor network adopting the sparsity exploitation physical layer is evaluated based on the network simulator 3 (NS-3) simulation tool. The simulation time-varying channel is generated by incorporating the Bellhop channel model with the statistical characteristics extracted from experimental shallow water channels. Three types of physical layers, i.e., those do not adopt sparse exploitation, adopting compressed sensing (CS), as well as the dynamic CS (DCS) technique, are employed for evaluation and comparison of network behavior under different media access control (MAC) protocols. The evaluation results verify the effectiveness of sparsity exploitation in improving UWA sensor network performance in the presence of time variations, while giving a quantitative comparison between enhancement achieved by the CS and DCS sparsity exploitation.</description><identifier>ISSN: 2327-4662</identifier><identifier>EISSN: 2327-4662</identifier><identifier>DOI: 10.1109/JIOT.2021.3094818</identifier><identifier>CODEN: IITJAU</identifier><language>eng</language><publisher>Piscataway: IEEE</publisher><subject>Access control ; Channel estimation ; Channels ; Estimation ; Exploitation ; Internet of Things ; Matching pursuit algorithms ; Media Access Protocol ; Network simulator 3 (NS-3) ; Physical layer ; Protocols ; Sensors ; Shallow water ; Simulation ; Sparsity ; sparsity exploitation ; time varying ; underwater acoustic (UWA) channel ; Underwater acoustics ; UWA sensor network</subject><ispartof>IEEE internet of things journal, 2022-02, Vol.9 (4), p.2859-2869</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2022</rights><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c293t-91aa05dd310785132a18e9ceb1d5cb06a4a2f122d4fe6cb882c70c4faa1dcb753</citedby><cites>FETCH-LOGICAL-c293t-91aa05dd310785132a18e9ceb1d5cb06a4a2f122d4fe6cb882c70c4faa1dcb753</cites><orcidid>0000-0003-4312-6108 ; 0000-0002-4959-2743</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/9475492$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,776,780,792,27901,27902,54733</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/9475492$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Jiang, Weihua</creatorcontrib><creatorcontrib>Tong, Feng</creatorcontrib><title>Exploiting Sparsity for Underwater Acoustic Sensor Network Under Time-Varying Channels</title><title>IEEE internet of things journal</title><addtitle>JIoT</addtitle><description>As a time-frequency doubly selective channel, severe multipath, Doppler, as well as the large time-delay characteristics of the underwater acoustic (UWA) channel pose significant challenge to the research and design of UWA communication and network systems. To mitigate these negative factors, inherent sparsity contained in the UWA channel has been extensively investigated to improve UWA communication via a sparsity exploitation receiver. While the performance of the UWA sensor network is highly dependent on that of the physical layer, there are few investigations reported on exploiting channel sparsity from the viewpoint of UWA networking. In this article, a UWA sensor network adopting the sparsity exploitation physical layer is evaluated based on the network simulator 3 (NS-3) simulation tool. The simulation time-varying channel is generated by incorporating the Bellhop channel model with the statistical characteristics extracted from experimental shallow water channels. Three types of physical layers, i.e., those do not adopt sparse exploitation, adopting compressed sensing (CS), as well as the dynamic CS (DCS) technique, are employed for evaluation and comparison of network behavior under different media access control (MAC) protocols. The evaluation results verify the effectiveness of sparsity exploitation in improving UWA sensor network performance in the presence of time variations, while giving a quantitative comparison between enhancement achieved by the CS and DCS sparsity exploitation.</description><subject>Access control</subject><subject>Channel estimation</subject><subject>Channels</subject><subject>Estimation</subject><subject>Exploitation</subject><subject>Internet of Things</subject><subject>Matching pursuit algorithms</subject><subject>Media Access Protocol</subject><subject>Network simulator 3 (NS-3)</subject><subject>Physical layer</subject><subject>Protocols</subject><subject>Sensors</subject><subject>Shallow water</subject><subject>Simulation</subject><subject>Sparsity</subject><subject>sparsity exploitation</subject><subject>time varying</subject><subject>underwater acoustic (UWA) channel</subject><subject>Underwater acoustics</subject><subject>UWA sensor network</subject><issn>2327-4662</issn><issn>2327-4662</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNpNkE1PwzAMhiMEEtPYD0BcKnHuiJOmbY7TNGBoYod9XKM0daFja0rSaezf06oT4mRLfl7begi5BzoGoPLpbb5cjxllMOZURimkV2TAOEvCKI7Z9b_-loy831FK25gAGQ_IdvZT723ZlNVHsKq182VzDgrrgk2VozvpBl0wMfbom9IEK6x8O3rH5mTdV48E6_KA4Va7c7di-qmrCvf-jtwUeu9xdKlDsnmeraev4WL5Mp9OFqFhkjehBK2pyHMONEkFcKYhRWkwg1yYjMY60qwAxvKowNhkacpMQk1UaA25yRLBh-Sx31s7-31E36idPbqqPalYzASPhWC8paCnjLPeOyxU7cpD-7ICqjqDqjOoOoPqYrDNPPSZEhH_eBklIpKM_wK7XW1H</recordid><startdate>20220215</startdate><enddate>20220215</enddate><creator>Jiang, Weihua</creator><creator>Tong, Feng</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><orcidid>https://orcid.org/0000-0003-4312-6108</orcidid><orcidid>https://orcid.org/0000-0002-4959-2743</orcidid></search><sort><creationdate>20220215</creationdate><title>Exploiting Sparsity for Underwater Acoustic Sensor Network Under Time-Varying Channels</title><author>Jiang, Weihua ; Tong, Feng</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c293t-91aa05dd310785132a18e9ceb1d5cb06a4a2f122d4fe6cb882c70c4faa1dcb753</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Access control</topic><topic>Channel estimation</topic><topic>Channels</topic><topic>Estimation</topic><topic>Exploitation</topic><topic>Internet of Things</topic><topic>Matching pursuit algorithms</topic><topic>Media Access Protocol</topic><topic>Network simulator 3 (NS-3)</topic><topic>Physical layer</topic><topic>Protocols</topic><topic>Sensors</topic><topic>Shallow water</topic><topic>Simulation</topic><topic>Sparsity</topic><topic>sparsity exploitation</topic><topic>time varying</topic><topic>underwater acoustic (UWA) channel</topic><topic>Underwater acoustics</topic><topic>UWA sensor network</topic><toplevel>online_resources</toplevel><creatorcontrib>Jiang, Weihua</creatorcontrib><creatorcontrib>Tong, Feng</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>Computer and Information Systems Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>IEEE internet of things journal</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Jiang, Weihua</au><au>Tong, Feng</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Exploiting Sparsity for Underwater Acoustic Sensor Network Under Time-Varying Channels</atitle><jtitle>IEEE internet of things journal</jtitle><stitle>JIoT</stitle><date>2022-02-15</date><risdate>2022</risdate><volume>9</volume><issue>4</issue><spage>2859</spage><epage>2869</epage><pages>2859-2869</pages><issn>2327-4662</issn><eissn>2327-4662</eissn><coden>IITJAU</coden><abstract>As a time-frequency doubly selective channel, severe multipath, Doppler, as well as the large time-delay characteristics of the underwater acoustic (UWA) channel pose significant challenge to the research and design of UWA communication and network systems. To mitigate these negative factors, inherent sparsity contained in the UWA channel has been extensively investigated to improve UWA communication via a sparsity exploitation receiver. While the performance of the UWA sensor network is highly dependent on that of the physical layer, there are few investigations reported on exploiting channel sparsity from the viewpoint of UWA networking. In this article, a UWA sensor network adopting the sparsity exploitation physical layer is evaluated based on the network simulator 3 (NS-3) simulation tool. The simulation time-varying channel is generated by incorporating the Bellhop channel model with the statistical characteristics extracted from experimental shallow water channels. Three types of physical layers, i.e., those do not adopt sparse exploitation, adopting compressed sensing (CS), as well as the dynamic CS (DCS) technique, are employed for evaluation and comparison of network behavior under different media access control (MAC) protocols. The evaluation results verify the effectiveness of sparsity exploitation in improving UWA sensor network performance in the presence of time variations, while giving a quantitative comparison between enhancement achieved by the CS and DCS sparsity exploitation.</abstract><cop>Piscataway</cop><pub>IEEE</pub><doi>10.1109/JIOT.2021.3094818</doi><tpages>11</tpages><orcidid>https://orcid.org/0000-0003-4312-6108</orcidid><orcidid>https://orcid.org/0000-0002-4959-2743</orcidid></addata></record> |
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subjects | Access control Channel estimation Channels Estimation Exploitation Internet of Things Matching pursuit algorithms Media Access Protocol Network simulator 3 (NS-3) Physical layer Protocols Sensors Shallow water Simulation Sparsity sparsity exploitation time varying underwater acoustic (UWA) channel Underwater acoustics UWA sensor network |
title | Exploiting Sparsity for Underwater Acoustic Sensor Network Under Time-Varying Channels |
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