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Record W2110585393 · doi:10.1109/tbc.2014.2304134

Raptor-Like Rate Compatible LDPC Codes and Their Puncturing Performance for the Cloud Transmission System

2014· article· en· W2110585393 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIEEE Transactions on Broadcasting · 2014
Typearticle
Languageen
FieldComputer Science
TopicError Correcting Code Techniques
Canadian institutionsCommunications Research Centre Canada
Fundersnot available
KeywordsLow-density parity-check codePuncturingTurbo codeRaptor codeForward error correctionComputer scienceConcatenated error correction codeCode wordSerial concatenated convolutional codesAlgorithmBlock codeElectronic engineeringDecoding methodsTelecommunicationsError floorEngineering

Abstract

fetched live from OpenAlex

This paper proposes a class of raptor-like rate compatible low-density parity check (LDPC) codes for the cloud transmission (CTxN) system. The proposed LDPC codes have lengths of 16,200 and 64,800 which are the same as those of DVB T2/S2 LDPC codes so that the CTxn system can easily be combined with the DVB-T2/S2 system for a second layer service. As the proposed LDPC codes are optimized at low coding rate range (R <;1/2), their performance is not only close to the Shannon limit, but also better than the DVB-T2/S2 LDPC codes. Moreover, the proposed LDPC codes have raptor code's property so that they can be decoded with a punctured codeword at the receiver for power saving and less latency under high signal-to-noise ratio regions.

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.

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)0.001
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.943
Threshold uncertainty score0.927

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.022
GPT teacher head0.231
Teacher spread0.209 · 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