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Hossein R. Sarrafzadeh

dblp:61/5036 · DBLP profile ↗
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2ranked-venue papers
2as first author
0since 2021 · last 2009
—ORCID · none

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

Computer networks · 2 · 2 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 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Physical-layer communications
channel coding
0.112007
State Transparent Convolutional Codes and Their Novel Maximum-Likelihood Decoding Algorithm · IEEE Trans. Commun. 2007
Physical-layer communications › channel coding › error control coding
convolutional codes
0.112007
State Transparent Convolutional Codes and Their Novel Maximum-Likelihood Decoding Algorithm · IEEE Trans. Commun. 2007
Physical-layer communications › channel coding › decoding algorithms
maximum-likelihood decoding
0.112007
State Transparent Convolutional Codes and Their Novel Maximum-Likelihood Decoding Algorithm · IEEE Trans. Commun. 2007

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

viterbi algorithm · 0.1trellis decoding · 0.1
YearPublicationVenuePosition
2009 Correction to "State Transparent Convolutional Codes and Their Novel Maximum-likelihood Decoding Algorithm" [Oct 07 1837-1844]
abstract
In the above titled paper (ibid., vol. 55, no. 10, pp. 1837-1844, Oct. 09), there was a typographical error on page 1839. The incorrect text and the corrected text appear here.
Hossein R. Sarrafzadeh
IEEE Trans. Commun.1
2007 State Transparent Convolutional Codes and Their Novel Maximum-Likelihood Decoding Algorithm
abstract
Almost all the probabilistic decoding algorithms known for convolutional codes, perform decoding without prior knowledge of the error locations. Here, we introduce a novel maximum-likelihood decoding algorithm for a new class of convolutional codes named as the state transparent convolutional (STC) codes, which due to their properties error detection and error locating is possible prior to error correction. Hence, their decoding algorithm, termed here as the STC decoder, allows an error correcting algorithm to be applied only to the erroneous portions of the received sequence referred to here as the error spans (ESPs). We further prove that the proposed decoder, which locates the ESPs and applies the Viterbi algorithm (VA) only to these portions, always yields a decoded path in trellis identical to the one generated by the Viterbi decoder (VD). Due to the fact that the STC decoder applies the VA only to the ESPs, hence percentage of the single-stage (per codeword) trellis decoding performed by the STC decoder is considerably less than the VD, which is applied to the entire received sequence and this reduction is overwhelming for the fading channels, where the erroneous codewords are mostly clustered. Furthermore, through applying the VA only to the ESPs, the resulting algorithm can be viewed as a new formulation of the VD for the STC codes that analogous to the block decoding algorithms provides a predecoding error detection and error locating capabilities, while performing less single-stage trellis decoding.
Hossein R. Sarrafzadeh
IEEE Trans. Commun.1