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Record W2149165695 · doi:10.1109/icc.2000.853283

Higher order adaptive filter based predistortion for nonlinear distortion compensation of radio over fiber links

2002· article· en· W2149165695 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
TopicSemiconductor Lasers and Optical Devices
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsPredistortionRadio over fiberFilter (signal processing)Compensation (psychology)Distortion (music)Computer scienceElectronic engineeringNonlinear distortionAdaptive filterControl theory (sociology)WirelessTelecommunicationsEngineeringBandwidth (computing)Artificial intelligence

Abstract

fetched live from OpenAlex

The biggest limitation of radio over fiber (ROF) links in a wireless network is its limited dynamic range due to 'non-linear distortions' (NLD). In this paper a higher order adaptive filter based modeling and predistortion scheme is proposed to compensate this NLD. The filter is adapted from the distortions of vector-modulated symbols, so that no in-depth knowledge of physical link parameters is needed. Experimental and simulation results show that a third order filter accurately models the ROF link while a second order filter adequately compensates for the phase nonlinearity. The power handling capability of the laser diode is the upper limit in this approach.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.584
Threshold uncertainty score0.997

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)0.0040.000

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 head0.025
GPT teacher head0.218
Teacher spread0.194 · 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

Citations42
Published2002
Admission routes1
Has abstractyes

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