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Record W2545422760 · doi:10.1109/acssc.2010.5757597

A new algorithm for sidelobe suppression and performance comparison in DFT-OFDM cognitive radios

2010· article· en· W2545422760 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 institutionsCommunications Research Centre CanadaMemorial University of Newfoundland
Fundersnot available
KeywordsOrthogonal frequency-division multiplexingCognitive radioOverhead (engineering)Bandwidth (computing)Computer scienceAlgorithmDiscrete Fourier transform (general)Electronic engineeringMultiplexingFourier transformTelecommunicationsMathematicsEngineeringWirelessFractional Fourier transform

Abstract

fetched live from OpenAlex

In this paper, we propose a novel algorithm to reduce the out-of-band radiation for the Discrete Fourier Transform (DFT)-based orthogonal frequency division multiplexing (OFDM) cognitive radio (CR) systems. Further, we provide a performance comparison for the proposed and conventional algorithms in terms of power spectral density (PSD), peak to average power ratio (PAPR), and required bandwidth for overhead. Simulation results demonstrate that the proposed algorithm outperforms the conventional algorithms at the cost of an overhead, with a similar PAPR. The trade-off between the PSD (as a benefit) and the PAPR and overhead (as costs) is emphasized, being used for the selection of specific algorithm parameters.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.965
Threshold uncertainty score0.420

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 head0.011
GPT teacher head0.260
Teacher spread0.248 · 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

Citations2
Published2010
Admission routes1
Has abstractyes

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