MétaCan
Menu
Back to cohort
Record W1984892955 · doi:10.1109/mwsym.2007.380356

A Bi-Directional Electronically Tunable CMOS Phase Shifter Using the High-Pass Topology

2007· article· en· W1984892955 on OpenAlexafffund
Mahmoud A. Abdalla, Khoman Phang, George V. Eleftheriades

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAntenna Design and Analysis
Canadian institutionsUniversity of Toronto
FundersCMC Microsystems
KeywordsPhase shift moduleVaricapInductorTopology (electrical circuits)Return lossCMOSElectronic engineeringElectrical engineeringComputer scienceEngineeringAntenna (radio)Insertion lossPhysicsCapacitance

Abstract

fetched live from OpenAlex

This paper presents an integrated phase shifter based on the high-pass L-C topology. The circuit utilizes both varactors and active inductors to extend the tuning range and achieve a low return loss. The high-pass topology results in a compact IC implementation, and allows phase compensation in series-fed antenna arrays utilizing this phase shifter. Furthermore, this approach allows integrating multiple stages on the same IC, without a significant size increase. A negative resistance is generated by the active inductor circuit, and is used to partially compensate the varactor losses. A test chip is fabricated in a standard 0.13μm CMOS process, and a phase tuning range of 96° is achieved at 4GHz, with a return loss better than -18dB across the entire tuning range. The phase shifter achieves a -2.2dBm input compression point and a 7.4dBm IIP3 while operating from a 1.5V supply.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

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 communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.012
GPT teacher head0.259
Teacher spread0.247 · 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 designNot applicable
Domainnot available
GenreMethods

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

Citations6
Published2007
Admission routes2
Has abstractyes

Explore more

Same topicAntenna Design and AnalysisFrench-language works237,207