## 2012 |

Campo, Adria Tauste; Vazquez-Vilar, Gonzalo; i Fàbregas, Albert Guillen; Koch, Tobias; Martinez, Alfonso Random Coding Bounds that Attain the Joint Source-Channel Exponent Inproceedings 2012 46th Annual Conference on Information Sciences and Systems (CISS), pp. 1–5, IEEE, Princeton, 2012, ISBN: 978-1-4673-3140-1. Abstract | Links | BibTeX | Tags: code construction, combined source-channel coding, Csiszár error exponent, Ducts, error probability, error statistics, Gallager exponent, joint source-channel coding, joint source-channel exponent, random codes, random-coding upper bound, Yttrium @inproceedings{Campo2012, title = {Random Coding Bounds that Attain the Joint Source-Channel Exponent}, author = {Adria Tauste Campo and Gonzalo Vazquez-Vilar and Albert Guillen i Fàbregas and Tobias Koch and Alfonso Martinez}, url = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6310910}, isbn = {978-1-4673-3140-1}, year = {2012}, date = {2012-01-01}, booktitle = {2012 46th Annual Conference on Information Sciences and Systems (CISS)}, pages = {1--5}, publisher = {IEEE}, address = {Princeton}, abstract = {This paper presents a random-coding upper bound on the average error probability of joint source-channel coding that attains Csiszár's error exponent. The bound is based on a code construction for which source messages are assigned to disjoint subsets (classes), and codewords are generated according to a distribution that depends on the class of the source message. For a single class, the bound recovers Gallager's exponent; identifying the classes with source type classes, it recovers Csiszár's exponent. Moreover, it is shown that as a two appropriately designed classes are sufficient to attain Csiszár's exponent.}, keywords = {code construction, combined source-channel coding, Csiszár error exponent, Ducts, error probability, error statistics, Gallager exponent, joint source-channel coding, joint source-channel exponent, random codes, random-coding upper bound, Yttrium}, pubstate = {published}, tppubtype = {inproceedings} } This paper presents a random-coding upper bound on the average error probability of joint source-channel coding that attains Csiszár's error exponent. The bound is based on a code construction for which source messages are assigned to disjoint subsets (classes), and codewords are generated according to a distribution that depends on the class of the source message. For a single class, the bound recovers Gallager's exponent; identifying the classes with source type classes, it recovers Csiszár's exponent. Moreover, it is shown that as a two appropriately designed classes are sufficient to attain Csiszár's exponent. |

Campo, Adria Tauste; Vazquez-Vilar, Gonzalo; i Fabregas, Albert Guillen; Koch, Tobias; Martinez, Alfonso Achieving Csiszár's Source-Channel Coding Exponent with Product Distributions Inproceedings 2012 IEEE International Symposium on Information Theory Proceedings, pp. 1548–1552, IEEE, Cambridge, MA, 2012, ISSN: 2157-8095. Abstract | Links | BibTeX | Tags: average probability of error, Channel Coding, code construction, codewords, Csiszár's source-channel coding, Decoding, Encoding, error probability, error statistics, Joints, Manganese, product distributions, random codes, random-coding upper bound, source coding, source messages, Upper bound @inproceedings{Campo2012a, title = {Achieving Csiszár's Source-Channel Coding Exponent with Product Distributions}, author = {Adria Tauste Campo and Gonzalo Vazquez-Vilar and Albert Guillen i Fabregas and Tobias Koch and Alfonso Martinez}, url = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6283524}, issn = {2157-8095}, year = {2012}, date = {2012-01-01}, booktitle = {2012 IEEE International Symposium on Information Theory Proceedings}, pages = {1548--1552}, publisher = {IEEE}, address = {Cambridge, MA}, abstract = {We derive a random-coding upper bound on the average probability of error of joint source-channel coding that recovers Csiszár's error exponent when used with product distributions over the channel inputs. Our proof technique for the error probability analysis employs a code construction for which source messages are assigned to subsets and codewords are generated with a distribution that depends on the subset.}, keywords = {average probability of error, Channel Coding, code construction, codewords, Csiszár's source-channel coding, Decoding, Encoding, error probability, error statistics, Joints, Manganese, product distributions, random codes, random-coding upper bound, source coding, source messages, Upper bound}, pubstate = {published}, tppubtype = {inproceedings} } We derive a random-coding upper bound on the average probability of error of joint source-channel coding that recovers Csiszár's error exponent when used with product distributions over the channel inputs. Our proof technique for the error probability analysis employs a code construction for which source messages are assigned to subsets and codewords are generated with a distribution that depends on the subset. |