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Multi-Edge-Type Low-Density Parity-Check Codes for Bandwidth-Efficient Modulation

2012· article· en· W2088111058 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 Communications · 2012
Typearticle
Languageen
FieldComputer Science
TopicError Correcting Code Techniques
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsLow-density parity-check codeComputer scienceAlgorithmBit error rateModulation (music)Error detection and correctionElectronic engineeringTurbo codeBlock codeLinear codeBandwidth (computing)Theoretical computer scienceMathematicsDecoding methodsTelecommunicationsEngineering

Abstract

fetched live from OpenAlex

A method of designing low-density parity-check codes for bandwidth-efficient high-order modulation is proposed. A multi-edge-type LDPC code ensemble is used to improve the correspondence between modulation bit-channel capacity and bit-level protection in a bit-interleaved coded modulation system. A key innovation is the development of a multi-dimensional extrinsic information transfer (EXIT) vector field technique for the analysis and design of multi-edge-type codes. A condition, sufficient for the decoder to converge, is derived on the multi-dimensional EXIT vector field, and this condition is used as a constraint in code optimization. Code designs indicate that the proposed method produces codes matching the performance of codes designed using best available methods in ensemble threshold, and is capable of achieving identical finite-length error rates with shorter block-lengths. In addition to simplified design complexity, the resulting codes allow for low-complexity implementation and rate-adaptivity, and hence are well-suited for adaptive modulation systems.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.769
Threshold uncertainty score0.908

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0020.000
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 head0.070
GPT teacher head0.330
Teacher spread0.260 · 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