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Record W2541446203 · doi:10.1109/icspc.2007.4728498

SLM-Based Radix FFT for PAPR Reduction in OFDM Systems

2007· article· en· W2541446203 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 Victoria
Fundersnot available
KeywordsFast Fourier transformOrthogonal frequency-division multiplexingDecimationReduction (mathematics)Radix (gastropod)AlgorithmComputer scienceComputational complexity theoryMultiplicative functionMathematicsArithmeticElectronic engineeringTelecommunicationsEngineering

Abstract

fetched live from OpenAlex

A radix FFT-based selective mapping (SLM) technique for reducing the peak-to-average power ratio (PAPR) of an orthogonal frequency division multiplexing (OFDM) signal is introduced. The intermediate signals within an N-point IFFT using a radix decimation in time (DIT) or decimation in frequency (DIF) IFFT algorithm are used for multiplying the phase sequences. Multiple IFFTs are then applied to the remaining stages. It is shown that DIF provides low multiplicative complexity in generating the SLM sequences compared to DIT, with the same PAPR reduction. In addition, a high radix FFT algorithm provides better PAPR reduction performance per stage with less multiplicative complexity compared to low radix algorithms.

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.461
Threshold uncertainty score0.452

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 head0.013
GPT teacher head0.239
Teacher spread0.227 · 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

Citations7
Published2007
Admission routes1
Has abstractyes

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