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Record W2108759449 · doi:10.1109/vtcf.2006.200

Adaptive Reed-Solomon Coding Scheme for OFDM Systems Over Frequency-Selective Fading Channels

2006· article· en· W2108759449 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 Vehicular Technology Conference · 2006
Typearticle
Languageen
FieldEngineering
TopicAdvanced Wireless Communication Techniques
Canadian institutionsMcGill University
Fundersnot available
KeywordsFadingComputer scienceOrthogonal frequency-division multiplexingTransmitterCoding (social sciences)Link adaptationFrequency domainElectronic engineeringChannel state informationAdaptive codingChannel (broadcasting)Reed–Solomon error correctionAlgorithmChannel codeTelecommunicationsDecoding methodsBlock codeMathematicsWirelessEngineeringConcatenated error correction codeStatisticsData compression

Abstract

fetched live from OpenAlex

This paper discusses an adaptive modulation/coding (AMC) strategy based on frequency-domain channel statistical information for OFDM systems in a frequency-selective fading environment. The proposed approach is based on the fact that the statistical properties of a time-varying channel vary very slowly with time and thus it is possible to obtain reliable knowledge at the transmitter. A programmable Reed-Solomon RS (n,k) code used with an adaptive multi-level modulation scheme is proposed as an illustrative example. Derivations of the frequency-domain channel statistical properties and performance of the proposed technique are presented along with illustrative results.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.834
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.019
GPT teacher head0.245
Teacher spread0.226 · 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