MétaCan
Menu
Back to cohort
Record W2158410083 · doi:10.1109/mwsym.2011.5972832

24-GHz joint radar and radio system capable of time-agile wireless sensing and communication

2011· article· en· W2158410083 on OpenAlexaff
Liang Han, Ke Wu

Bibliographic record

Venue2011 IEEE MTT-S International Microwave Symposium · 2011
Typearticle
Languageen
FieldEngineering
TopicVehicular Ad Hoc Networks (VANETs)
Canadian institutionsUniversité de MontréalPolytechnique Montréal
Fundersnot available
KeywordsPhase-shift keyingElectronic engineeringComputer scienceWirelessCommunications systemTransceiverRadarKeyingEngineeringTelecommunicationsBit error rateChannel (broadcasting)

Abstract

fetched live from OpenAlex

A multifunctional and time-agile system combining both radar sensing and radio communication capabilities is proposed and experimentally demonstrated for 24-GHz vehicular applications. By arranging the radar sensing mode and the radio communication mode in sequential time slots, the present system can operate with the flexibility and capability of functional reconfiguration and fusion using a single transceiver platform. To further reduce cost and also increase efficiency, a 24-GHz system demonstrator has been designed based on the substrate integrated waveguide (SIW) technology. Preliminary experiments have verified system performance. In addition to high-precision range detection, the proposed system has proved a great capability of communication at a data rate of 50 Mbps for both binary-phase-shift-keying (BPSK) and quadrature-phase-shift-keying (QPSK). Therefore, this system is a very promising cost-effective solution for the development of 24-GHz onboard multifunctional systems.

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: Empirical
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)0.0010.000
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)0.0020.001

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 head0.011
GPT teacher head0.174
Teacher spread0.163 · 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

Citations8
Published2011
Admission routes1
Has abstractyes

Explore more

Same venue2011 IEEE MTT-S International Microwave SymposiumSame topicVehicular Ad Hoc Networks (VANETs)French-language works237,207