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Record W2309497218

Low distortion transmission of 802.11a/n signals in amplified radio over fibre links with modulator bias optimization

2007· article· en· W2309497218 on OpenAlexaff
Marco Michele Sisto, F. Vacondio, Sophie LaRochelle, Leslie A. Rusch

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Photonic Communication Systems
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsIntermodulationElectro-optic modulatorDistortion (music)AmplifierLinearityElectronic engineeringSpurious-free dynamic rangeNonlinear distortionTransmission (telecommunications)RF power amplifierTelecommunicationsComputer scienceOptical modulatorEngineeringCMOSPhase modulation
DOInot available

Abstract

fetched live from OpenAlex

In this work, we study the propagation of an IEEE 802.11a/n compliant signal over an analog optical link employing a Mach-Zehnder modulator, an Erbium doped fibre amplifier and 10 km of standard fibre. We show that, when the bias of the modulator is controlled in order to maximize the received RF power at the end of the link, the link linearity can also be improved. This is due to the interaction between the distortion caused by the Mach-Zehnder and the fibre nonlinearities. We simulate and measure the link intermodulation distortion (ID3) as a function of the modulator bias, showing in which condi-tions it is possible to simultaneously minimize the ID3 and maximize the link gain. Also, we show that the error vector magnitude, an important quality factor of OFDM IEEE 802.11a/n signals, can greatly benefit from the im-proved link linearity. Thus, the bias optimization allows for both higher power and higher quality transmission with respect to standard quadrature biased links. KEY WORDS ROF links, wireless signals on optical link, fibre nonlin-earities, Mach-Zehnder nonlinearities.

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 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: none
Teacher disagreement score0.787
Threshold uncertainty score0.474

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 head0.016
GPT teacher head0.240
Teacher spread0.224 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations1
Published2007
Admission routes1
Has abstractyes

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