Achieving 1/2 log (1+SNR) on the AWGN channel with lattice encoding and decoding
We address an open question, regarding whether a lattice code with lattice decoding (as opposed to maximum-likelihood (ML) decoding) can achieve the additive white Gaussian noise (AWGN) channel capacity. We first demonstrate how minimum mean-square error (MMSE) scaling along with dithering (lattice...
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Veröffentlicht in: | IEEE transactions on information theory 2004-10, Vol.50 (10), p.2293-2314 |
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description | We address an open question, regarding whether a lattice code with lattice decoding (as opposed to maximum-likelihood (ML) decoding) can achieve the additive white Gaussian noise (AWGN) channel capacity. We first demonstrate how minimum mean-square error (MMSE) scaling along with dithering (lattice randomization) techniques can transform the power-constrained AWGN channel into a modulo-lattice additive noise channel, whose effective noise is reduced by a factor of /spl radic/(1+SNR/SNR). For the resulting channel, a uniform input maximizes mutual information, which in the limit of large lattice dimension becomes 1/2 log (1+SNR), i.e., the full capacity of the original power constrained AWGN channel. We then show that capacity may also be achieved using nested lattice codes, the coarse lattice serving for shaping via the modulo-lattice transformation, the fine lattice for channel coding. We show that such pairs exist for any desired nesting ratio, i.e., for any signal-to-noise ratio (SNR). Furthermore, for the modulo-lattice additive noise channel lattice decoding is optimal. Finally, we show that the error exponent of the proposed scheme is lower bounded by the Poltyrev exponent. |
doi_str_mv | 10.1109/TIT.2004.834787 |
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We first demonstrate how minimum mean-square error (MMSE) scaling along with dithering (lattice randomization) techniques can transform the power-constrained AWGN channel into a modulo-lattice additive noise channel, whose effective noise is reduced by a factor of /spl radic/(1+SNR/SNR). For the resulting channel, a uniform input maximizes mutual information, which in the limit of large lattice dimension becomes 1/2 log (1+SNR), i.e., the full capacity of the original power constrained AWGN channel. We then show that capacity may also be achieved using nested lattice codes, the coarse lattice serving for shaping via the modulo-lattice transformation, the fine lattice for channel coding. We show that such pairs exist for any desired nesting ratio, i.e., for any signal-to-noise ratio (SNR). Furthermore, for the modulo-lattice additive noise channel lattice decoding is optimal. Finally, we show that the error exponent of the proposed scheme is lower bounded by the Poltyrev exponent.</description><identifier>ISSN: 0018-9448</identifier><identifier>EISSN: 1557-9654</identifier><identifier>DOI: 10.1109/TIT.2004.834787</identifier><identifier>CODEN: IETTAW</identifier><language>eng</language><publisher>New York, NY: IEEE</publisher><subject>Additive noise ; Additive white noise ; Applied sciences ; AWGN channels ; Channel capacity ; Codes ; Coding, codes ; Exact sciences and technology ; Gaussian noise ; Information, signal and communications theory ; Lattice theory ; Lattices ; Maximum likelihood decoding ; Mean square errors ; Mutual information ; Noise reduction ; Normal distribution ; Signal and communications theory ; Signal to noise ratio ; Systems, networks and services of telecommunications ; Telecommunications ; Telecommunications and information theory ; Transmission and modulation (techniques and equipments)</subject><ispartof>IEEE transactions on information theory, 2004-10, Vol.50 (10), p.2293-2314</ispartof><rights>2005 INIST-CNRS</rights><rights>Copyright Institute of Electrical and Electronics Engineers, Inc. (IEEE) Oct 2004</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/1337105$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,780,784,796,27924,27925,54758</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/1337105$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=16170617$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Erez, U.</creatorcontrib><creatorcontrib>Zamir, R.</creatorcontrib><title>Achieving 1/2 log (1+SNR) on the AWGN channel with lattice encoding and decoding</title><title>IEEE transactions on information theory</title><addtitle>TIT</addtitle><description>We address an open question, regarding whether a lattice code with lattice decoding (as opposed to maximum-likelihood (ML) decoding) can achieve the additive white Gaussian noise (AWGN) channel capacity. We first demonstrate how minimum mean-square error (MMSE) scaling along with dithering (lattice randomization) techniques can transform the power-constrained AWGN channel into a modulo-lattice additive noise channel, whose effective noise is reduced by a factor of /spl radic/(1+SNR/SNR). For the resulting channel, a uniform input maximizes mutual information, which in the limit of large lattice dimension becomes 1/2 log (1+SNR), i.e., the full capacity of the original power constrained AWGN channel. We then show that capacity may also be achieved using nested lattice codes, the coarse lattice serving for shaping via the modulo-lattice transformation, the fine lattice for channel coding. We show that such pairs exist for any desired nesting ratio, i.e., for any signal-to-noise ratio (SNR). Furthermore, for the modulo-lattice additive noise channel lattice decoding is optimal. Finally, we show that the error exponent of the proposed scheme is lower bounded by the Poltyrev exponent.</description><subject>Additive noise</subject><subject>Additive white noise</subject><subject>Applied sciences</subject><subject>AWGN channels</subject><subject>Channel capacity</subject><subject>Codes</subject><subject>Coding, codes</subject><subject>Exact sciences and technology</subject><subject>Gaussian noise</subject><subject>Information, signal and communications theory</subject><subject>Lattice theory</subject><subject>Lattices</subject><subject>Maximum likelihood decoding</subject><subject>Mean square errors</subject><subject>Mutual information</subject><subject>Noise reduction</subject><subject>Normal distribution</subject><subject>Signal and communications theory</subject><subject>Signal to noise ratio</subject><subject>Systems, networks and services of telecommunications</subject><subject>Telecommunications</subject><subject>Telecommunications and information theory</subject><subject>Transmission and modulation (techniques and equipments)</subject><issn>0018-9448</issn><issn>1557-9654</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2004</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNpdzktLw0AQB_BFFKyPswcvi6AoknZnk30dS_EFUkUrHsPuZtJuiZuapIrf3kgFwcMwDPObP0PIEbAhADOj2d1syBnLhjrNlFZbZABCqMRIkW2TAWOgE5Nlepfste2yHzMBfEAex34R8CPEOYURp1U9p-dw-Tx9uqB1pN0C6fj1Zkr9wsaIFf0M3YJWtuuCR4rR18XPpY0FLXAzHJCd0lYtHv72ffJyfTWb3Cb3Dzd3k_F9EriELgEhuea2dIZL61NrtXPCKJQFovNWOlYY4EqDddI5l6EDk6rUgTa6NCVP98nZJnfV1O9rbLv8LbQeq8pGrNdt3qczwTLRw5N_cFmvm9j_loMR2nAlWY9Of5Ftva3KxkYf2nzVhDfbfOUgQbG-ene8cQER_9ZpqoCJ9BtFe3Fz</recordid><startdate>20041001</startdate><enddate>20041001</enddate><creator>Erez, U.</creator><creator>Zamir, R.</creator><general>IEEE</general><general>Institute of Electrical and Electronics Engineers</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>RIA</scope><scope>RIE</scope><scope>IQODW</scope><scope>7SC</scope><scope>7SP</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope></search><sort><creationdate>20041001</creationdate><title>Achieving 1/2 log (1+SNR) on the AWGN channel with lattice encoding and decoding</title><author>Erez, U. ; Zamir, R.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i261t-156282afb926ac3aa8bb597e6deebca6b0d912781ab6bbb4eb19373b1898f9f23</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2004</creationdate><topic>Additive noise</topic><topic>Additive white noise</topic><topic>Applied sciences</topic><topic>AWGN channels</topic><topic>Channel capacity</topic><topic>Codes</topic><topic>Coding, codes</topic><topic>Exact sciences and technology</topic><topic>Gaussian noise</topic><topic>Information, signal and communications theory</topic><topic>Lattice theory</topic><topic>Lattices</topic><topic>Maximum likelihood decoding</topic><topic>Mean square errors</topic><topic>Mutual information</topic><topic>Noise reduction</topic><topic>Normal distribution</topic><topic>Signal and communications theory</topic><topic>Signal to noise ratio</topic><topic>Systems, networks and services of telecommunications</topic><topic>Telecommunications</topic><topic>Telecommunications and information theory</topic><topic>Transmission and modulation (techniques and equipments)</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Erez, U.</creatorcontrib><creatorcontrib>Zamir, R.</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>Pascal-Francis</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & 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_linktorsrc</fulltext></delivery><addata><au>Erez, U.</au><au>Zamir, R.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Achieving 1/2 log (1+SNR) on the AWGN channel with lattice encoding and decoding</atitle><jtitle>IEEE transactions on information theory</jtitle><stitle>TIT</stitle><date>2004-10-01</date><risdate>2004</risdate><volume>50</volume><issue>10</issue><spage>2293</spage><epage>2314</epage><pages>2293-2314</pages><issn>0018-9448</issn><eissn>1557-9654</eissn><coden>IETTAW</coden><abstract>We address an open question, regarding whether a lattice code with lattice decoding (as opposed to maximum-likelihood (ML) decoding) can achieve the additive white Gaussian noise (AWGN) channel capacity. We first demonstrate how minimum mean-square error (MMSE) scaling along with dithering (lattice randomization) techniques can transform the power-constrained AWGN channel into a modulo-lattice additive noise channel, whose effective noise is reduced by a factor of /spl radic/(1+SNR/SNR). For the resulting channel, a uniform input maximizes mutual information, which in the limit of large lattice dimension becomes 1/2 log (1+SNR), i.e., the full capacity of the original power constrained AWGN channel. We then show that capacity may also be achieved using nested lattice codes, the coarse lattice serving for shaping via the modulo-lattice transformation, the fine lattice for channel coding. We show that such pairs exist for any desired nesting ratio, i.e., for any signal-to-noise ratio (SNR). Furthermore, for the modulo-lattice additive noise channel lattice decoding is optimal. Finally, we show that the error exponent of the proposed scheme is lower bounded by the Poltyrev exponent.</abstract><cop>New York, NY</cop><pub>IEEE</pub><doi>10.1109/TIT.2004.834787</doi><tpages>22</tpages></addata></record> |
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subjects | Additive noise Additive white noise Applied sciences AWGN channels Channel capacity Codes Coding, codes Exact sciences and technology Gaussian noise Information, signal and communications theory Lattice theory Lattices Maximum likelihood decoding Mean square errors Mutual information Noise reduction Normal distribution Signal and communications theory Signal to noise ratio Systems, networks and services of telecommunications Telecommunications Telecommunications and information theory Transmission and modulation (techniques and equipments) |
title | Achieving 1/2 log (1+SNR) on the AWGN channel with lattice encoding and decoding |
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