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Nir Binshtok

dblp:53/10936 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 1999
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Computer networks · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Theoretical computer science
1 paper
Coding theory · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Coding theory › error-correcting codes
coded modulation
0.011999
Integer metrics for binary input symmetric output memoryless channels · IEEE Trans. Commun. 1999
Coding theory › channel coding › error exponent
cutoff rate
0.011999
Integer metrics for binary input symmetric output memoryless channels · IEEE Trans. Commun. 1999
Coding theory › error-correcting codes › decoding › channel decoding
mismatched decoding
0.011999
Integer metrics for binary input symmetric output memoryless channels · IEEE Trans. Commun. 1999

Methods — techniques the papers use, named apart from their topics

integer metric optimization · 0.0
YearPublicationVenuePosition
1999 Integer metrics for binary input symmetric output memoryless channels
abstract
Consider a coded communication system where antipodal signaling is used over symmetric memoryless channels. A mismatch decoder employing metrics which assume values in a finite set of integers is used. Two performance measures for achievable rates are considered, the generalized cutoff rate and the mismatch capacity. Two different integer metric assignments which maximize these criteria are found. The optimal metric assignment holds for any binary input symmetric output memoryless channels. It is calculated explicitly for the faded additive white Gaussian noise channel with and without diversity, an interference channel model and the additive "Cauchy" channel. The difference in terms of achievable rates between decoding using the optimal continuous metric and integer metric is calculated for these channels. The degradation for fairly low number of quantization levels is found to be small, e.g. for nine quantization levels degradation is less than 0.3 dB for all analyzed channels. The sensitivity of the generalized cutoff rate and the mismatch capacity to the exact location of the quantization levels is rather mild. The difference between the mismatch capacity corresponding to the optimal integer quantization and the mismatch capacity obtained by the quantization which optimizes the generalized cutoff rate is found to be quite small.
Nir Binshtok, Shlomo Shamai
IEEE Trans. Commun.1