DocumentCode
1780383
Title
List decoding - Random coding exponents and expurgated exponents
Author
Merhav, Neri
Author_Institution
Dept. of Electr. Eng., Technion - Israel Inst. of Technol., Haifa, Israel
fYear
2014
fDate
June 29 2014-July 4 2014
Firstpage
2459
Lastpage
2463
Abstract
New results are derived concerning random coding error exponents and expurgated exponents for list decoding with a deterministic list size L. Two asymptotic regimes are considered, the fixed list-size regime, where L is fixed independently of the block length n, and the exponential list-size, where L grows exponentially with n. We first derive a general upper bound on the list-decoding average error probability, which is suitable for both regimes. This bound leads to more specific bounds in the two regimes. In the fixed list-size regime, the bound is related to known bounds and we establish its exponential tightness. In the exponential list-size regime, we establish the achievability of the well known sphere packing lower bound. An immediate byproduct of our analysis in both regimes is the universality of the maximum mutual information (MMI) list decoder in the error exponent sense. Finally, we consider expurgated bounds at low rates, using the Csiszár-Körner-Marton approach. This expurgated bound, which involves the notion of multi-information, is also modified to apply to continuous alphabet channels, and in particular, to the Gaussian memoryless channel, where the expression of the expurgated bound becomes quite explicit.
Keywords
Gaussian channels; channel coding; coding errors; error statistics; memoryless systems; random codes; Csiszar-Korner-Marton approach; Gaussian memoryless channel; MMI list decoder; asymptotic regimes; continuous alphabet channels; deterministic list size; exponential list size regime; expurgated bound; expurgated exponents; fixed list size regime; list decoding average error probability; maximum mutual information; random coding error exponents; sphere packing lower bound; upper bound; Channel coding; Decoding; Entropy; Upper bound; Vectors;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Theory (ISIT), 2014 IEEE International Symposium on
Conference_Location
Honolulu, HI
Type
conf
DOI
10.1109/ISIT.2014.6875276
Filename
6875276
Link To Document