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Record W2113750761 · doi:10.1155/2009/508678

Millimeter-Wave Ultra-Wideband Six-Port Receiver Using Cross-Polarized Antennas

2009· article· en· W2113750761 on OpenAlexafffund
Nazih Khaddaj Mallat, E. Moldovan, Ke Wu, Serioja Ovidiu Tatu

Bibliographic record

VenueEURASIP Journal on Wireless Communications and Networking · 2009
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsInstitut National de la Recherche ScientifiquePolytechnique MontréalUniversité du Québec à Montréal
FundersFonds Québécois de la Recherche sur la Nature et les Technologies
KeywordsComputer scienceTransmitterTransceiverUltra-widebandTransmission (telecommunications)Radio receiver designWidebandElectronic engineeringExtremely high frequencyElectrical engineeringTelecommunicationsWirelessChannel (broadcasting)Engineering

Abstract

fetched live from OpenAlex

This paper presents a new low-cost millimeter-wave ultra-wideband (UWB) transceiver architecture operating over V-band from 60 to 64 GHz. Since the local oscillator (LO) power required in the operation of six-port receiver is generally low (compared to conventional one using diode mixers), the carrier recovery or LO synchronization is avoided by using second transmission path and cross-polarized antennas. The six-port model used in system simulation is based on -parameters measurements of a rectangular waveguide hybrid coupler. The receiver architecture is validated by comparisons between transmitter and receiver bit sequences and bit error rate results of 500 Mb/s pseudorandom QPSK signal.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.004

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 integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.002

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 head0.042
GPT teacher head0.271
Teacher spread0.229 · 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 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

Citations7
Published2009
Admission routes2
Has abstractyes

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