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Record W2127391113 · doi:10.1109/rfic.2002.1011945

Ka-band direct digital receiver using 0.25 /spl mu/m GaAs PHEMTs

2002· article· en· W2127391113 on OpenAlexaff
Serioja Ovidiu Tatu, E. Moldovan, G. Brehm, Ke Wu, R.G. Bosisio

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicRadio Frequency Integrated Circuit Design
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsRadio receiver designRF front endElectrical engineeringAmplifierElectronic engineeringLocal Multipoint Distribution ServiceLocal oscillatorComputer scienceWidebandDirect-conversion receiverSuperheterodyne receiverWirelessEngineeringTelecommunicationsAntenna (radio)Phase noiseCMOSRadio frequencyDetectorChannel (broadcasting)Transmitter

Abstract

fetched live from OpenAlex

A new direct conversion wideband (26 GHz - 28.5 GHz) six-port millimeter wave receiver using MMIC technology is proposed to meet the needs of mass-market wireless communications. This six-port receiver is designed to operate without the need for precise power reading and the use of digital signal processor (DSP) that is usually required in other receivers. The proposed receiver architecture is chosen to satisfy requirements of hardware receiver used in QPSK communications. The receiver contains one MMIC module consisting of a wide band six-port junction with four RF Schottky detectors, a receiver front-end and a base hand module composed of video amplifiers and I&Q decoder. The maximum bit rate, at least 100 Mbs, is determined solely by the limiting speed of ancillary video amplifiers and analogue decoder. This new hardware receiver is proposed as a robust, rugged, low cost receiver for use in wide Ka-band wireless mass market QPSK communications such as LMDS services that are a prime example of communication equipment requiring such receivers. BER results are presented in the presence of noise and local oscillator (LO) phase shift.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
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 communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.002

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 head0.030
GPT teacher head0.198
Teacher spread0.168 · 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 designOther design
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
Published2002
Admission routes1
Has abstractyes

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