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Record W2093276172 · doi:10.1109/glocomw.2011.6162559

Receiver design for asymmetrically clipped optical OFDM

2011· article· en· W2093276172 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
TopicOptical Wireless Communication Technologies
Canadian institutionsMcMaster University
Fundersnot available
KeywordsClipping (morphology)Orthogonal frequency-division multiplexingBandlimitingComputer scienceDetectorOptical wirelessNoise (video)Signal-to-noise ratio (imaging)Electronic engineeringModulation (music)Optical powerAlgorithmTelecommunicationsChannel (broadcasting)WirelessPhysicsOpticsEngineeringArtificial intelligenceAcousticsImage (mathematics)

Abstract

fetched live from OpenAlex

Asymmetrically clipped optical OFDM (ACO-OFDM) is compatible with optical intensity modulation and is well suited to bandlimited optical wireless channels. By carefully locating data on odd subcarriers and clipping the resulting time signal, ACO-OFDM guarantees non-negative output amplitudes and clipping noise orthogonal to the information. However, in the conventional receiver, clipping noise is ignored in detection and data are extracted from odd subcarriers only. In this paper, a new receiver design for ACO-OFDM is proposed which exploits the structure of the clipping noise to improve the optical power efficiency. By observing the anti-symmetry of time domain samples, a simple pairwise maximum likelihood detector is developed and is used to fix half of the received samples to zero. Simulation results show that employing the proposed detector design leads to 1.3 dB optical gain at a BER of 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-5</sup> .

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.626
Threshold uncertainty score0.370

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 head0.095
GPT teacher head0.241
Teacher spread0.147 · 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