Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

Andrey Kreimer

dblp:226/7309 · DBLP profile ↗
← Back
1ranked-venue papers
1as first author
0since 2021 · last 2018
0000-0002-3940-7049ORCID · reported

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%
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
Coding theory
channel coding
0.312018
Efficient Low-Complexity Phase Noise Resistant Iterative Joint Phase Estimation and Decoding Algorithm · IEEE Trans. Commun. 2018
Coding theory › error-correcting codes › graph-based codes
turbo codes and LDPC codes
0.312018
Efficient Low-Complexity Phase Noise Resistant Iterative Joint Phase Estimation and Decoding Algorithm · IEEE Trans. Commun. 2018
Physical-layer communications › synchronization › carrier recovery
carrier phase estimation
0.112018
Efficient Low-Complexity Phase Noise Resistant Iterative Joint Phase Estimation and Decoding Algorithm · IEEE Trans. Commun. 2018
Physical-layer communications › synchronization
phase noise
0.112018
Efficient Low-Complexity Phase Noise Resistant Iterative Joint Phase Estimation and Decoding Algorithm · IEEE Trans. Commun. 2018

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

gaussian approximation · 0.7belief propagation · 0.7
YearPublicationVenuePosition
2018 Efficient Low-Complexity Phase Noise Resistant Iterative Joint Phase Estimation and Decoding Algorithm
abstract
In this paper, we present a new low-complexity iterative joint phase estimation and decoding algorithm which can be applied to low-density-parity-check (or turbo) codes for channels affected by strong phase noise. The algorithm exhibits a very good performance and a very low complexity even in strong phase noise, high code rate, and high-order constellations. The proposed algorithm works by first obtaining a preliminary pilots-aided phase estimation. Next, the expressions for the belief propagation messages are approximated around that reference and reduced to a Gaussian canonical form. This results in a simple closed form of a recursive update. Simulations results for phase-shift-keying modulation of size 8 and quadrature-amplitude modulation of size 64 are presented and compared with other algorithms in the literature.
Andrey Kreimer, Dan Raphaeli
IEEE Trans. Commun.1