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Reliable and Secure Multishot Network Coding Using Linearized Reed-Solomon Codes

Multishot network coding is considered in a worst-case adversarial setting in which an omniscient adversary with unbounded computational resources may inject erroneous packets in up to t links, erase up to \rho packets, and wire-tap up to \mu links, all throughout \ell shots of a linearly-co...

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Published in:IEEE transactions on information theory 2019-08, Vol.65 (8), p.4785-4803
Main Authors: Martinez-Penas, Umberto, Kschischang, Frank R.
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description Multishot network coding is considered in a worst-case adversarial setting in which an omniscient adversary with unbounded computational resources may inject erroneous packets in up to t links, erase up to \rho packets, and wire-tap up to \mu links, all throughout \ell shots of a linearly-coded network. Assuming no knowledge of the underlying linear network code (in particular, the network topology and underlying linear code may be random and change with time), a coding scheme achieving zero-error communication and perfect secrecy is obtained based on linearized Reed-Solomon codes. The scheme achieves the maximum possible secret message size of \ell n^\prime - 2t - \rho - \mu packets for coherent communication, where n^\prime is the number of outgoing links at the source, for any packet length m \geq n^\prime (largest possible range). By lifting this construction, coding schemes for non-coherent communication are obtained with information rates close to optimal for practical instances. The required field size is q^{m} , where q > \ell , thus q^{m} \approx \ell ^{n^\prime } , which is always smaller than that of a Gabidulin code tailored for \ell shots, which would be at least 2^{\ell n^\prime } . A Welch-Berlekamp sum-rank decoding algorithm for linearized Reed-Solomon codes is provided, having quadratic complexity in the total length n = \ell n^\prime , and which can be adapted to handle not only errors but also erasures, wire-tap observations and non-coherent communication. Combined with the obtained field size, the given decodi
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Assuming no knowledge of the underlying linear network code (in particular, the network topology and underlying linear code may be random and change with time), a coding scheme achieving zero-error communication and perfect secrecy is obtained based on linearized Reed-Solomon codes. The scheme achieves the maximum possible secret message size of <inline-formula> <tex-math notation="LaTeX">\ell n^\prime - 2t - \rho - \mu </tex-math></inline-formula> packets for coherent communication, where <inline-formula> <tex-math notation="LaTeX">n^\prime </tex-math></inline-formula> is the number of outgoing links at the source, for any packet length <inline-formula> <tex-math notation="LaTeX">m \geq n^\prime </tex-math></inline-formula> (largest possible range). By lifting this construction, coding schemes for non-coherent communication are obtained with information rates close to optimal for practical instances. The required field size is <inline-formula> <tex-math notation="LaTeX">q^{m} </tex-math></inline-formula>, where <inline-formula> <tex-math notation="LaTeX">q > \ell </tex-math></inline-formula>, thus <inline-formula> <tex-math notation="LaTeX">q^{m} \approx \ell ^{n^\prime } </tex-math></inline-formula>, which is always smaller than that of a Gabidulin code tailored for <inline-formula> <tex-math notation="LaTeX">\ell </tex-math></inline-formula> shots, which would be at least <inline-formula> <tex-math notation="LaTeX">2^{\ell n^\prime } </tex-math></inline-formula>. A Welch-Berlekamp sum-rank decoding algorithm for linearized Reed-Solomon codes is provided, having quadratic complexity in the total length <inline-formula> <tex-math notation="LaTeX">n = \ell n^\prime </tex-math></inline-formula>, and which can be adapted to handle not only errors but also erasures, wire-tap observations and non-coherent communication. Combined with the obtained field size, the given decoding complexity is of <inline-formula> <tex-math notation="LaTeX">\mathcal {O}(n^{\prime 4} \ell ^{2} \log (\ell)^{2}) </tex-math></inline-formula> operations in <inline-formula> <tex-math notation="LaTeX">\mathbb {F}_{2} </tex-math></inline-formula>, whereas the most efficient known decoding algorithm for a Gabidulin code has a complexity of <inline-formula> <tex-math notation="LaTeX">\mathcal {O}(n^{\prime 3.69} \ell ^{3.69} \log (\ell)^{2}) </tex-math></inline-formula> operations in <inline-formula> <tex-math notation="LaTeX">\mathbb {F}_{2} </tex-math></inline-formula>, assuming a multiplication in a finite field <inline-formula> <tex-math notation="LaTeX">\mathbb {F} </tex-math></inline-formula> costs about <inline-formula> <tex-math notation="LaTeX">\log (|\mathbb {F}|)^{2} </tex-math></inline-formula> operations in <inline-formula> <tex-math notation="LaTeX">\mathbb {F}_{2} </tex-math></inline-formula>.]]></description><identifier>ISSN: 0018-9448</identifier><identifier>EISSN: 1557-9654</identifier><identifier>DOI: 10.1109/TIT.2019.2912165</identifier><identifier>CODEN: IETTAW</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Algorithms ; Codes ; Coding ; Coherence ; Communication ; Complexity ; Complexity theory ; Decoding ; Encoding ; Fields (mathematics) ; Knowledge engineering ; Knowledge management ; Linearization ; Linearized Reed-Solomon codes ; Links ; Multiplication ; multishot network coding ; Network coding ; network error-correction ; Network topologies ; Packets (communication) ; Reed-Solomon codes ; Reliability ; sum-rank metric ; sum-subspace codes ; Wire ; wire-tap channel ; Wiretapping</subject><ispartof>IEEE transactions on information theory, 2019-08, Vol.65 (8), p.4785-4803</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2019</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c291t-d1ca40bc65a3b5257e6e3bc32bc9159b1b6a66e755ce40a89eefe862575df23e3</citedby><cites>FETCH-LOGICAL-c291t-d1ca40bc65a3b5257e6e3bc32bc9159b1b6a66e755ce40a89eefe862575df23e3</cites><orcidid>0000-0003-2626-8139 ; 0000-0002-4274-1785</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/8694869$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,780,784,27924,27925,54796</link.rule.ids></links><search><creatorcontrib>Martinez-Penas, Umberto</creatorcontrib><creatorcontrib>Kschischang, Frank R.</creatorcontrib><title>Reliable and Secure Multishot Network Coding Using Linearized Reed-Solomon Codes</title><title>IEEE transactions on information theory</title><addtitle>TIT</addtitle><description><![CDATA[Multishot network coding is considered in a worst-case adversarial setting in which an omniscient adversary with unbounded computational resources may inject erroneous packets in up to <inline-formula> <tex-math notation="LaTeX">t </tex-math></inline-formula> links, erase up to <inline-formula> <tex-math notation="LaTeX">\rho </tex-math></inline-formula> packets, and wire-tap up to <inline-formula> <tex-math notation="LaTeX">\mu </tex-math></inline-formula> links, all throughout <inline-formula> <tex-math notation="LaTeX">\ell </tex-math></inline-formula> shots of a linearly-coded network. Assuming no knowledge of the underlying linear network code (in particular, the network topology and underlying linear code may be random and change with time), a coding scheme achieving zero-error communication and perfect secrecy is obtained based on linearized Reed-Solomon codes. The scheme achieves the maximum possible secret message size of <inline-formula> <tex-math notation="LaTeX">\ell n^\prime - 2t - \rho - \mu </tex-math></inline-formula> packets for coherent communication, where <inline-formula> <tex-math notation="LaTeX">n^\prime </tex-math></inline-formula> is the number of outgoing links at the source, for any packet length <inline-formula> <tex-math notation="LaTeX">m \geq n^\prime </tex-math></inline-formula> (largest possible range). By lifting this construction, coding schemes for non-coherent communication are obtained with information rates close to optimal for practical instances. The required field size is <inline-formula> <tex-math notation="LaTeX">q^{m} </tex-math></inline-formula>, where <inline-formula> <tex-math notation="LaTeX">q > \ell </tex-math></inline-formula>, thus <inline-formula> <tex-math notation="LaTeX">q^{m} \approx \ell ^{n^\prime } </tex-math></inline-formula>, which is always smaller than that of a Gabidulin code tailored for <inline-formula> <tex-math notation="LaTeX">\ell </tex-math></inline-formula> shots, which would be at least <inline-formula> <tex-math notation="LaTeX">2^{\ell n^\prime } </tex-math></inline-formula>. A Welch-Berlekamp sum-rank decoding algorithm for linearized Reed-Solomon codes is provided, having quadratic complexity in the total length <inline-formula> <tex-math notation="LaTeX">n = \ell n^\prime </tex-math></inline-formula>, and which can be adapted to handle not only errors but also erasures, wire-tap observations and non-coherent communication. Combined with the obtained field size, the given decoding complexity is of <inline-formula> <tex-math notation="LaTeX">\mathcal {O}(n^{\prime 4} \ell ^{2} \log (\ell)^{2}) </tex-math></inline-formula> operations in <inline-formula> <tex-math notation="LaTeX">\mathbb {F}_{2} </tex-math></inline-formula>, whereas the most efficient known decoding algorithm for a Gabidulin code has a complexity of <inline-formula> <tex-math notation="LaTeX">\mathcal {O}(n^{\prime 3.69} \ell ^{3.69} \log (\ell)^{2}) </tex-math></inline-formula> operations in <inline-formula> <tex-math notation="LaTeX">\mathbb {F}_{2} </tex-math></inline-formula>, assuming a multiplication in a finite field <inline-formula> <tex-math notation="LaTeX">\mathbb {F} </tex-math></inline-formula> costs about <inline-formula> <tex-math notation="LaTeX">\log (|\mathbb {F}|)^{2} </tex-math></inline-formula> operations in <inline-formula> <tex-math notation="LaTeX">\mathbb {F}_{2} </tex-math></inline-formula>.]]></description><subject>Algorithms</subject><subject>Codes</subject><subject>Coding</subject><subject>Coherence</subject><subject>Communication</subject><subject>Complexity</subject><subject>Complexity theory</subject><subject>Decoding</subject><subject>Encoding</subject><subject>Fields (mathematics)</subject><subject>Knowledge engineering</subject><subject>Knowledge management</subject><subject>Linearization</subject><subject>Linearized Reed-Solomon codes</subject><subject>Links</subject><subject>Multiplication</subject><subject>multishot network coding</subject><subject>Network coding</subject><subject>network error-correction</subject><subject>Network topologies</subject><subject>Packets (communication)</subject><subject>Reed-Solomon codes</subject><subject>Reliability</subject><subject>sum-rank metric</subject><subject>sum-subspace codes</subject><subject>Wire</subject><subject>wire-tap channel</subject><subject>Wiretapping</subject><issn>0018-9448</issn><issn>1557-9654</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><recordid>eNo9kN1LwzAQwIMoOKfvgi8FnztzaZM2jzJ0DuYH-3gOaXrVzq6ZSYvoX2_Khg93x8HvPvgRcg10AkDl3Xq-njAKcsIkMBD8hIyA8yyWgqenZEQp5LFM0_ycXHi_DW3KgY3I2xKbWhcNRrotoxWa3mH03Ddd7T9sF71g923dZzS1Zd2-Rxs_5EXdonb1L5bRErGMV7axO9sOEPpLclbpxuPVsY7J5vFhPX2KF6-z-fR-EZvwYBeXYHRKCyO4TgrOeIYCk8IkrDASuCygEFoIzDg3mFKdS8QKcxFAXlYswWRMbg97985-9eg7tbW9a8NJxZiAPBcZsEDRA2Wc9d5hpfau3mn3o4CqwZsK3tTgTR29hZGbw0iNiP94LmQaIvkDTz9pJw</recordid><startdate>20190801</startdate><enddate>20190801</enddate><creator>Martinez-Penas, Umberto</creator><creator>Kschischang, Frank R.</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>7SP</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><orcidid>https://orcid.org/0000-0003-2626-8139</orcidid><orcidid>https://orcid.org/0000-0002-4274-1785</orcidid></search><sort><creationdate>20190801</creationdate><title>Reliable and Secure Multishot Network Coding Using Linearized Reed-Solomon Codes</title><author>Martinez-Penas, Umberto ; Kschischang, Frank R.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c291t-d1ca40bc65a3b5257e6e3bc32bc9159b1b6a66e755ce40a89eefe862575df23e3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Algorithms</topic><topic>Codes</topic><topic>Coding</topic><topic>Coherence</topic><topic>Communication</topic><topic>Complexity</topic><topic>Complexity theory</topic><topic>Decoding</topic><topic>Encoding</topic><topic>Fields (mathematics)</topic><topic>Knowledge engineering</topic><topic>Knowledge management</topic><topic>Linearization</topic><topic>Linearized Reed-Solomon codes</topic><topic>Links</topic><topic>Multiplication</topic><topic>multishot network coding</topic><topic>Network coding</topic><topic>network error-correction</topic><topic>Network topologies</topic><topic>Packets (communication)</topic><topic>Reed-Solomon codes</topic><topic>Reliability</topic><topic>sum-rank metric</topic><topic>sum-subspace codes</topic><topic>Wire</topic><topic>wire-tap channel</topic><topic>Wiretapping</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Martinez-Penas, Umberto</creatorcontrib><creatorcontrib>Kschischang, Frank R.</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>Electronics &amp; Communications 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 transactions on information theory</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Martinez-Penas, Umberto</au><au>Kschischang, Frank R.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Reliable and Secure Multishot Network Coding Using Linearized Reed-Solomon Codes</atitle><jtitle>IEEE transactions on information theory</jtitle><stitle>TIT</stitle><date>2019-08-01</date><risdate>2019</risdate><volume>65</volume><issue>8</issue><spage>4785</spage><epage>4803</epage><pages>4785-4803</pages><issn>0018-9448</issn><eissn>1557-9654</eissn><coden>IETTAW</coden><abstract><![CDATA[Multishot network coding is considered in a worst-case adversarial setting in which an omniscient adversary with unbounded computational resources may inject erroneous packets in up to <inline-formula> <tex-math notation="LaTeX">t </tex-math></inline-formula> links, erase up to <inline-formula> <tex-math notation="LaTeX">\rho </tex-math></inline-formula> packets, and wire-tap up to <inline-formula> <tex-math notation="LaTeX">\mu </tex-math></inline-formula> links, all throughout <inline-formula> <tex-math notation="LaTeX">\ell </tex-math></inline-formula> shots of a linearly-coded network. Assuming no knowledge of the underlying linear network code (in particular, the network topology and underlying linear code may be random and change with time), a coding scheme achieving zero-error communication and perfect secrecy is obtained based on linearized Reed-Solomon codes. The scheme achieves the maximum possible secret message size of <inline-formula> <tex-math notation="LaTeX">\ell n^\prime - 2t - \rho - \mu </tex-math></inline-formula> packets for coherent communication, where <inline-formula> <tex-math notation="LaTeX">n^\prime </tex-math></inline-formula> is the number of outgoing links at the source, for any packet length <inline-formula> <tex-math notation="LaTeX">m \geq n^\prime </tex-math></inline-formula> (largest possible range). By lifting this construction, coding schemes for non-coherent communication are obtained with information rates close to optimal for practical instances. The required field size is <inline-formula> <tex-math notation="LaTeX">q^{m} </tex-math></inline-formula>, where <inline-formula> <tex-math notation="LaTeX">q > \ell </tex-math></inline-formula>, thus <inline-formula> <tex-math notation="LaTeX">q^{m} \approx \ell ^{n^\prime } </tex-math></inline-formula>, which is always smaller than that of a Gabidulin code tailored for <inline-formula> <tex-math notation="LaTeX">\ell </tex-math></inline-formula> shots, which would be at least <inline-formula> <tex-math notation="LaTeX">2^{\ell n^\prime } </tex-math></inline-formula>. A Welch-Berlekamp sum-rank decoding algorithm for linearized Reed-Solomon codes is provided, having quadratic complexity in the total length <inline-formula> <tex-math notation="LaTeX">n = \ell n^\prime </tex-math></inline-formula>, and which can be adapted to handle not only errors but also erasures, wire-tap observations and non-coherent communication. Combined with the obtained field size, the given decoding complexity is of <inline-formula> <tex-math notation="LaTeX">\mathcal {O}(n^{\prime 4} \ell ^{2} \log (\ell)^{2}) </tex-math></inline-formula> operations in <inline-formula> <tex-math notation="LaTeX">\mathbb {F}_{2} </tex-math></inline-formula>, whereas the most efficient known decoding algorithm for a Gabidulin code has a complexity of <inline-formula> <tex-math notation="LaTeX">\mathcal {O}(n^{\prime 3.69} \ell ^{3.69} \log (\ell)^{2}) </tex-math></inline-formula> operations in <inline-formula> <tex-math notation="LaTeX">\mathbb {F}_{2} </tex-math></inline-formula>, assuming a multiplication in a finite field <inline-formula> <tex-math notation="LaTeX">\mathbb {F} </tex-math></inline-formula> costs about <inline-formula> <tex-math notation="LaTeX">\log (|\mathbb {F}|)^{2} </tex-math></inline-formula> operations in <inline-formula> <tex-math notation="LaTeX">\mathbb {F}_{2} </tex-math></inline-formula>.]]></abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/TIT.2019.2912165</doi><tpages>19</tpages><orcidid>https://orcid.org/0000-0003-2626-8139</orcidid><orcidid>https://orcid.org/0000-0002-4274-1785</orcidid></addata></record>
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source IEEE Electronic Library (IEL) Journals
subjects Algorithms
Codes
Coding
Coherence
Communication
Complexity
Complexity theory
Decoding
Encoding
Fields (mathematics)
Knowledge engineering
Knowledge management
Linearization
Linearized Reed-Solomon codes
Links
Multiplication
multishot network coding
Network coding
network error-correction
Network topologies
Packets (communication)
Reed-Solomon codes
Reliability
sum-rank metric
sum-subspace codes
Wire
wire-tap channel
Wiretapping
title Reliable and Secure Multishot Network Coding Using Linearized Reed-Solomon Codes
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