Multiuser Random Coding Techniques for Mismatched Decoding

This paper studies multiuser random coding techniques for channel coding with a given (possibly suboptimal) decoding rule. For the mismatched discrete memoryless multiple-access channel, an error exponent is obtained that is tight with respect to the ensemble average, and positive within the interio...

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Vydáno v:IEEE transactions on information theory Ročník 62; číslo 7; s. 3950 - 3970
Hlavní autoři: Scarlett, Jonathan, Martinez, Alfonso, Guillen i Fabregas, Albert
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York IEEE 01.07.2016
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Institute of Electrical and Electronics Engineers (IEEE)
Témata:
Channels
Codes
Coding
Coding theory
Communication channels
Decoding
Electronic mail
Encoding
ensemble tightness
Equivalence
error exponents
Exponents
Indexes
Information theory
Lagrange duality
Maximum likelihood decoding
Measurement
Mismatched decoding
multiple-access channel
random coding
superposition coding
Tightness
maximum-likelihood decoding
multiple-access channel
Lagrange duality
error exponents
superposition coding
Mismatched decoding
random coding
ensemble tightness
ISSN:0018-9448, 1557-9654
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Popis
Shrnutí:This paper studies multiuser random coding techniques for channel coding with a given (possibly suboptimal) decoding rule. For the mismatched discrete memoryless multiple-access channel, an error exponent is obtained that is tight with respect to the ensemble average, and positive within the interior of Lapidoth's achievable rate region. This exponent proves the ensemble tightness of the exponent of Liu and Hughes in the case of maximum-likelihood decoding. An equivalent dual form of Lapidoth's achievable rate region is given, and the latter is shown to immediately extend to channels with infinite and continuous alphabets. In the setting of single-user mismatched decoding, similar analysis techniques are applied to a refined version of superposition coding, which is shown to achieve rates at least as high as standard superposition coding for any set of random-coding parameters.
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ISSN:0018-9448
1557-9654
DOI:10.1109/TIT.2016.2555317