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Record W2160095768 · doi:10.1109/glocom.2003.1258202

Application of reed-solomon codes with erasure decoding to type-II hybrid ARQ transmission

2004· article· en· W2160095768 on OpenAlexafffund
M.L.B. Riediger, P. Ho

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicCoding theory and cryptography
Canadian institutionsSimon Fraser University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsHybrid automatic repeat requestComputer scienceReed–Solomon error correctionErasureDecoding methodsAutomatic repeat requestSelective Repeat ARQError detection and correctionAlgorithmCode rateErasure codeConcatenated error correction codeBlock codeTransmission (telecommunications)Telecommunications

Abstract

fetched live from OpenAlex

Hybrid ARQ protocols are capable of improving the robustness and throughput of a mobile wireless communication system when a feedback channel is available. In this paper a type-II hybrid ARQ protocol is implemented with a punctured Reed-Solomon (RS) code to result in a rate-compatible system. It is proposed to use side-information provided by pilot symbols to flag symbol erasures, and perform erasure decoding of rate-compatible RS codes. Throughput simulation results show that when using errors-only decoding, rate-compatible punctured RS codes outperform their constituent punctured RS codes. When comparing errors-only decoding to erasure decoding of the rate-compatible RS codes, a power savings is observed when erasure decoding is employed. The specific gain achieved however, is dependant on the average signal-to-noise ratio and constituent set of punctured RS codes.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.008
GPT teacher head0.225
Teacher spread0.217 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations6
Published2004
Admission routes2
Has abstractyes

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