MétaCan
Menu
Back to cohort
Record W2095727436 · doi:10.1109/vetecs.2009.5073381

An Efficient PAPR Reduction Method for Wavelet Packet Modulation Schemes

2009· article· en· W2095727436 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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicPAPR reduction in OFDM
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsBasis (linear algebra)Reduction (mathematics)WaveletOrthogonal frequency-division multiplexingModulation (music)Wavelet packet decompositionComputer scienceNetwork packetBasis functionAlgorithmUpper and lower boundsOrthogonal basisMathematicsWavelet transformElectronic engineeringControl theory (sociology)Channel (broadcasting)TelecommunicationsEngineeringArtificial intelligenceAcoustics

Abstract

fetched live from OpenAlex

This paper proposes a novel peak-to-average power ratio (PAPR) reduction method for wavelet packet modulation (WPM) based multi-carrier systems. Orthogonal basis functions that minimize a newly derived PAPR upper bound are designed. The performance of the proposed orthogonal basis functions is compared to those of the conventional Daubechies basis functions and OFDM. Via these comparisons, it is shown that the proposed orthogonal basis functions achieve notable performance improvements over its comparatives.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.568
Threshold uncertainty score0.451

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 science0.0000.000
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 head0.015
GPT teacher head0.300
Teacher spread0.285 · 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

Quick stats

Citations8
Published2009
Admission routes1
Has abstractyes

Explore more

Same topicPAPR reduction in OFDMFrench-language works237,207