MétaCan
Menu
Back to cohort
Record W2903442432 · doi:10.23919/eumc.2018.8541722

Accurate Millimeter-wave Carrier Frequency Offset Measurement Using the Six-port Interferometric Technique

2018· article· en· W2903442432 on OpenAlexaff
Mansoor Dashti Ardakani, C. Hannachi, B. Zouggari, E. Moldovan, Serioja Ovidiu Tatu

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMicrowave and Dielectric Measurement Techniques
Canadian institutionsInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsInterferometryOffset (computer science)AmplitudeLocal oscillatorExtremely high frequencyCarrier frequency offsetFrequency offsetMillimeterCalibrationDoppler effectPhysicsOpticsRadio frequencyFrequency bandFrequency synthesizerPhase noiseBandwidth (computing)Computer scienceOrthogonal frequency-division multiplexingTelecommunicationsChannel (broadcasting)Phase-locked loop

Abstract

fetched live from OpenAlex

A V-band front-end based on a six-port interferometer is proposed for the accurate measurement of Carrier Frequency Offset (CFO) and carrier recovery in a wireless system. The interferometer uses power readings for amplitude, phase or frequency comparison between its two RF inputs. If the circuit is carefully designed, this low-cost technique allows precise phase and frequency measurements without the need of any calibration. Furthermore, the ability to work with a reduced local oscillator (LO) power is a significant advantage of interferometry versus conventional mixing techniques. Measurements performed at 64 GHz show a resolution of a few Hz, as low as permitted by today's DC coupled measurement equipment. A CFO of 3 Hz, equivalent with a Doppler shift corresponding to a velocity of 7 mm/s, has been successfully measured.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.934
Threshold uncertainty score0.876

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.083
GPT teacher head0.260
Teacher spread0.177 · 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 designBench or experimental
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

Citations16
Published2018
Admission routes1
Has abstractyes

Explore more

Same topicMicrowave and Dielectric Measurement TechniquesFrench-language works237,207