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Cuong Hon Lai

dblp:119/4699 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 1995
—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.

Computer networks
1 paper
Physical-layer communications · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Physical-layer communications
channel coding
0.011995
An efficient convolutional coding/decoding strategy for channels with memory · IEEE Trans. Commun. 1995
Physical-layer communications › channel coding › error control coding › convolutional codes
punctured convolutional codes
0.011995
An efficient convolutional coding/decoding strategy for channels with memory · IEEE Trans. Commun. 1995
Physical-layer communications
channel modeling
0.011995
An efficient convolutional coding/decoding strategy for channels with memory · IEEE Trans. Commun. 1995
Physical-layer communications › channel modeling
markov channel model
0.011995
An efficient convolutional coding/decoding strategy for channels with memory · IEEE Trans. Commun. 1995

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

upper bound analysis · 0.0performance analysis · 0.0
YearPublicationVenuePosition
1995 An efficient convolutional coding/decoding strategy for channels with memory
abstract
Many digital communication channels are affected by errors that tend to occur in bursts. A great deal of work has been devoted to finding good burst-error-correcting codes and developing burst-error-correcting schemes. However, burst-error-correcting codes are generally not effective for long bursts. Some burst-error-correcting schemes suffer long delay in decoding. Others are very sensitive to random errors in the guard space. Most of these schemes are not adaptive to channel conditions. A new adaptive scheme is proposed to overcome these drawbacks. The scheme employs a combination of two complementary punctured convolutional (CPC) codes. One of the codes is used for burst detection and for channel state estimation, and both codes are used for error correction. The proposed scheme is analyzed over a two state Markov chain channel model. Unlike existing burst-error-correcting schemes, it is shown that the proposed scheme is adaptive to channel conditions and less sensitive to errors in the guard space. For the same delay, the proposed scheme offers better performance than the interleaving schemes. When the channel is heavily corrupted by bursts, the improvement is even more pronounced.
Cuong Hon Lai, Samir Kallel
IEEE Trans. Commun.1