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Amir Mozammel

dblp:279/3393 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2023
0000-0003-3474-9530ORCID · reported

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

Computer networks · 1 · 1 since 2021

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 · 75% Graph algorithms and graph theory · 25%

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

TopicWeightPapersLastEvidence papers
Coding theory › error-correcting codes › decoding › decoding algorithms › low-complexity decoding
decoding complexity reduction
0.712023
A Tree Pruning Technique for Decoding Complexity Reduction of Polar Codes and PAC Codes · IEEE Trans. Commun. 2023
Coding theory › channel coding
polar codes
0.712023
A Tree Pruning Technique for Decoding Complexity Reduction of Polar Codes and PAC Codes · IEEE Trans. Commun. 2023
Coding theory › error-correcting codes › decoding › list decoding
successive cancellation list decoding
0.712023
A Tree Pruning Technique for Decoding Complexity Reduction of Polar Codes and PAC Codes · IEEE Trans. Commun. 2023
Graph algorithms and graph theory › graph algorithms › tree algorithms
tree pruning
0.712023
A Tree Pruning Technique for Decoding Complexity Reduction of Polar Codes and PAC Codes · IEEE Trans. Commun. 2023

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

stack algorithm · 0.7path metric analysis · 0.7
YearPublicationVenuePosition
2023 A Tree Pruning Technique for Decoding Complexity Reduction of Polar Codes and PAC Codes
abstract
Sorting operation is one of the main bottlenecks for the successive-cancellation list (SCL) decoding. This paper introduces an improvement to the SCL decoding for polar and pre-transformed polar codes that reduces the number of sorting operations without visible degradation in the code’s error-correction performance. In an SCL decoding with an optimum metric function we show that, on average, the correct branch’s bit-metric value must be equal to the bit-channel capacity, and on the other hand, the average bit-metric value of a wrong branch can be at most zero. This implies that a wrong path’s partial path metric value deviates from the bit-channel capacity’s partial summation. For relatively reliable bit-channels, the bit metric for a wrong branch becomes very large negative number, which enables us to detect and prune such paths. We prove that, for a threshold lower than the bit-channel cutoff rate, the probability of pruning the correct path decreases exponentially by the given threshold. Based on these findings, we presented a pruning technique, and the experimental results demonstrate a substantial decrease in the amount of sorting procedures required for SCL decoding. In the stack algorithm, a similar technique is used to significantly reduce the average number of paths in the stack.
Mohsen Moradi, Amir Mozammel
IEEE Trans. Commun.2