MétaCan
Menu
Back to cohort
Record W2068985238 · doi:10.1109/bmsb.2013.6621773

Quarter-rate LDPC code and its truncated performance for the cloud transmission

2013· article· en· W2068985238 on OpenAlexaff
Sung-Ik Park, Yiyan Wu, Heung Mook Kim, Liang Zhang, Jin-Ho Chung, Namho Hur, Jeongchang Kim

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicError Correcting Code Techniques
Canadian institutionsCommunications Research Centre Canada
Fundersnot available
KeywordsLow-density parity-check codeCode wordComputer scienceAdditive white Gaussian noiseCode rateConcatenated error correction codeCode (set theory)AlgorithmDecoding methodsChannel (broadcasting)Electronic engineeringReal-time computingTelecommunicationsBlock codeEngineering

Abstract

fetched live from OpenAlex

This paper explains the structure of a newly designed quarter-rate low density parity check (LDPC) code for the cloud transmission system, and presents its truncated performance under additive white Gaussian noise (AWGN) channel. Since new quarter-rate LDPC code has fountain code's property, at the receiver, it can be decoded with truncated codeword for power saving and less latency under high signal to noise ratio (SNR) regions. By computer simulation, the truncated LDPC code shows the same or worse performance compared with the dedicated DVB-T2/S2 LDPC code.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.921
Threshold uncertainty score0.285

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.020
GPT teacher head0.248
Teacher spread0.228 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2013
Admission routes1
Has abstractyes

Explore more

Same topicError Correcting Code TechniquesFrench-language works237,207