Generalized coset codes for distributed binning
In many multiterminal communication problems, constructions of good source codes involve finding distributed partitions (into bins) of a collection of quantizers associated with a group of source encoders. Further, computationally efficient procedures to index these bins are also required. In this w...
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Veröffentlicht in: | IEEE transactions on information theory 2005-10, Vol.51 (10), p.3457-3474 |
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description | In many multiterminal communication problems, constructions of good source codes involve finding distributed partitions (into bins) of a collection of quantizers associated with a group of source encoders. Further, computationally efficient procedures to index these bins are also required. In this work, we consider a constructive approach for distributed binning in an algebraic framework. Several application scenarios fall under the scope of this paper including the CEO problem, distributed source coding, and n-channel symmetric multiple description source coding with n>2. Specifically, in this exposition we consider the case of two codebooks while focusing on the Gaussian CEO problem with mean squared error reconstruction and with two symmetric observations. This problem deals with distributed encoding of correlated noisy observations of a source into descriptions such that the joint decoder having access to them can reconstruct the source with a fidelity criterion. We employ generalized coset codes constructed in a group-theoretic setting for this approach, and analyze the performance in terms of distance properties and decoding algorithms. |
doi_str_mv | 10.1109/TIT.2005.855584 |
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Further, computationally efficient procedures to index these bins are also required. In this work, we consider a constructive approach for distributed binning in an algebraic framework. Several application scenarios fall under the scope of this paper including the CEO problem, distributed source coding, and n-channel symmetric multiple description source coding with n>2. Specifically, in this exposition we consider the case of two codebooks while focusing on the Gaussian CEO problem with mean squared error reconstruction and with two symmetric observations. This problem deals with distributed encoding of correlated noisy observations of a source into descriptions such that the joint decoder having access to them can reconstruct the source with a fidelity criterion. 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(IEEE) Oct 2005</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c381t-9773635fd753d8e09de93f477f5c2fa864495078c54d208ae7b4bb54b1438a793</citedby><cites>FETCH-LOGICAL-c381t-9773635fd753d8e09de93f477f5c2fa864495078c54d208ae7b4bb54b1438a793</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/1512420$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,776,780,792,27903,27904,54736</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/1512420$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=17139369$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Pradhan, S.S.</creatorcontrib><creatorcontrib>Ramchandran, K.</creatorcontrib><title>Generalized coset codes for distributed binning</title><title>IEEE transactions on information theory</title><addtitle>TIT</addtitle><description>In many multiterminal communication problems, constructions of good source codes involve finding distributed partitions (into bins) of a collection of quantizers associated with a group of source encoders. Further, computationally efficient procedures to index these bins are also required. In this work, we consider a constructive approach for distributed binning in an algebraic framework. Several application scenarios fall under the scope of this paper including the CEO problem, distributed source coding, and n-channel symmetric multiple description source coding with n>2. Specifically, in this exposition we consider the case of two codebooks while focusing on the Gaussian CEO problem with mean squared error reconstruction and with two symmetric observations. This problem deals with distributed encoding of correlated noisy observations of a source into descriptions such that the joint decoder having access to them can reconstruct the source with a fidelity criterion. We employ generalized coset codes constructed in a group-theoretic setting for this approach, and analyze the performance in terms of distance properties and decoding algorithms.</description><subject>Algebra</subject><subject>Algorithm design and analysis</subject><subject>Algorithms</subject><subject>Applied sciences</subject><subject>Bins</subject><subject>CEO problem</subject><subject>Coding</subject><subject>Coding, codes</subject><subject>Communication networks</subject><subject>Communications systems</subject><subject>Computer programming</subject><subject>Construction</subject><subject>Decoding</subject><subject>Distributed source coding</subject><subject>Encoding</subject><subject>Exact sciences and technology</subject><subject>Focusing</subject><subject>Information resources</subject><subject>Information theory</subject><subject>Information, signal and communications theory</subject><subject>Instruments</subject><subject>multiple description source coding</subject><subject>Performance analysis</subject><subject>Quantization</subject><subject>random binning</subject><subject>Reconstruction</subject><subject>Sensor phenomena and characterization</subject><subject>Signal and communications theory</subject><subject>Source code</subject><subject>Source coding</subject><subject>Telecommunications and information theory</subject><subject>trellis cosets</subject><issn>0018-9448</issn><issn>1557-9654</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2005</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNp9kUFLAzEQhYMoWKtnD16KoJ62TTaTTXKUorVQ8FLPIZtNJGW7W5Pdg_56s2yh4MHLDMN878G8QeiW4DkhWC626-08x5jNBWNMwBmaEMZ4JgsG52iCMRGZBBCX6CrGXRqBkXyCFivb2KBr_2OrmWmj7VKtbJy5NswqH7vgy75Lu9I3jW8-r9GF03W0N8c-RR-vL9vlW7Z5X62Xz5vMUEG6THJOC8pcxRmthMWyspI64NwxkzstCgDJMBeGQZVjoS0voSwZlASo0FzSKXoafQ-h_ept7NTeR2PrWje27aOSBArIC4ET-fgvmQtMJCcigfd_wF3bhyZdoYhkEmMKA7QYIRPaGIN16hD8XodvRbAaclYpZzXkrMack-LhaKuj0bULujE-nmScUEmL4aK7kfPW2tM6fQFyTH8B3OWDXA</recordid><startdate>20051001</startdate><enddate>20051001</enddate><creator>Pradhan, S.S.</creator><creator>Ramchandran, K.</creator><general>IEEE</general><general>Institute of Electrical and Electronics Engineers</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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Further, computationally efficient procedures to index these bins are also required. In this work, we consider a constructive approach for distributed binning in an algebraic framework. Several application scenarios fall under the scope of this paper including the CEO problem, distributed source coding, and n-channel symmetric multiple description source coding with n>2. Specifically, in this exposition we consider the case of two codebooks while focusing on the Gaussian CEO problem with mean squared error reconstruction and with two symmetric observations. This problem deals with distributed encoding of correlated noisy observations of a source into descriptions such that the joint decoder having access to them can reconstruct the source with a fidelity criterion. 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subjects | Algebra Algorithm design and analysis Algorithms Applied sciences Bins CEO problem Coding Coding, codes Communication networks Communications systems Computer programming Construction Decoding Distributed source coding Encoding Exact sciences and technology Focusing Information resources Information theory Information, signal and communications theory Instruments multiple description source coding Performance analysis Quantization random binning Reconstruction Sensor phenomena and characterization Signal and communications theory Source code Source coding Telecommunications and information theory trellis cosets |
title | Generalized coset codes for distributed binning |
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