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Record W2099848737 · doi:10.1109/glocom.2008.ecp.675

Second-Order Cyclostationarity of Cyclically Prefixed Single Carrier Linear Digital Modulations with Applications to Signal Recognition

2008· article· en· W2099848737 on OpenAlexaff
Octavia A. Dobre, Q. Zhang, Sreeraman Rajan, Robert Inkol

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicWireless Signal Modulation Classification
Canadian institutionsDefence Research and Development CanadaMemorial University of Newfoundland
Fundersnot available
KeywordsWaveformSIGNAL (programming language)Orthogonal frequency-division multiplexingComputer scienceAlgorithmNoise (video)Signal processingSpeech recognitionElectronic engineeringDigital signal processingTelecommunicationsArtificial intelligenceEngineeringComputer hardware

Abstract

fetched live from OpenAlex

The second-order cyclostationarity of cyclically prefixed single carrier linear digital (CP-tSCLD) modulated signals is investigated with emphasis on its applicability to signal recognition. Analytical closed-form expressions for the second-order (one-conjugate) cyclic cumulants (CCs) and the set of cycle frequencies (CFs) for CP-SCLD modulated signals are derived. Based on these results, an algorithm is proposed for the recognition of CP-tSCLD against SCLD and orthogonal frequency division multiplexing (OFDM) signals. This algorithm obviates the need for signal pre-processing tasks, such as symbol timing, carrier and waveform recovery and estimation of signal and noise powers.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.045
GPT teacher head0.247
Teacher spread0.202 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations20
Published2008
Admission routes1
Has abstractyes

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