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Guangsong Wang

dblp:151/4605 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2014
—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 · 87% Information theory · 13%

Topics — the 6 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Coding theory › error-correcting codes
code construction
0.212014
Design of Irregular Repeat Accumulate Codes for Finite Decoder Iterations · IEEE Trans. Commun. 2014
Coding theory › error-correcting codes › LDPC codes
irregular repeat-accumulate codes
0.212014
Design of Irregular Repeat Accumulate Codes for Finite Decoder Iterations · IEEE Trans. Commun. 2014
Coding theory › error-correcting codes › decoding
iterative decoding
0.212014
Design of Irregular Repeat Accumulate Codes for Finite Decoder Iterations · IEEE Trans. Commun. 2014
Coding theory › error-correcting codes › graph-based codes
sparse-graph codes
0.212014
Design of Irregular Repeat Accumulate Codes for Finite Decoder Iterations · IEEE Trans. Commun. 2014
Information theory › communication channels › channel models › binary-input channel
binary erasure channel
0.112014
Design of Irregular Repeat Accumulate Codes for Finite Decoder Iterations · IEEE Trans. Commun. 2014
Information theory
channel capacity
0.112014
Design of Irregular Repeat Accumulate Codes for Finite Decoder Iterations · IEEE Trans. Commun. 2014

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

extrinsic information transfer analysis · 0.2code optimization · 0.2
YearPublicationVenuePosition
2014 Design of Irregular Repeat Accumulate Codes for Finite Decoder Iterations
abstract
This paper deals with the design of non-systematic irregular repeat-accumulate codes that are optimised for a finite number of decoding iterations. In many cases of practical interest, the usual approach for sparse-graph codes, which aims to approach capacity (with arbitrarily many decoder iterations), may not be suitable. This is of particular importance for systems with complexity or delay constraints. In this paper, we provide a design methodology which constrains the number of decoder iterations, as well as other measures of implementation complexity. Our approach uses extrinsic information transfer analysis, and our main contribution is the formulation of code optimisation problems which directly incorporate the number of iterations into the constraints. We focus on the single user binary erasure channel and the two-user binary adder channel, where this transfer analysis is exact. Generalisation to other sparse graph codes and other channels (under usual approximations) is straightforward.
Guangsong Wang, Ingmar Land, Alex J. Grant
IEEE Trans. Commun.1