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Record W2145580894 · doi:10.1109/lawp.2005.857299

A space-time coding scheme utilizing phase shifting antennas at RF frequencies

2005· article· en· W2145580894 on OpenAlexaff
Geoffrey G. Messier, Adrian Sutinjo, Sean V. Hum, M. Okoniewski

Bibliographic record

VenueIEEE Antennas and Wireless Propagation Letters · 2005
Typearticle
Languageen
FieldEngineering
TopicAdvanced Wireless Communication Techniques
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsCode division multiple accessComputer scienceElectronic engineeringSpace–time codeAmplifierCoding (social sciences)Radio frequencyBlock codeTelecommunicationsEngineeringMathematicsDecoding methodsBandwidth (computing)

Abstract

fetched live from OpenAlex

We introduce a new technique for performing space-time coding by using a phase shifting antenna feed network to manipulate the transmitted signal at RF frequencies. The advantage of this scheme is that it allows space-time coding to be implemented with only one transmit chain and amplifier. A code-division multiple-access (CDMA) system that can use this method of space-time coding is described. The antenna feed network is presented along with a modified version of the Alamouti code that is suitable for this application. Imperfections in the antenna phase shifting are quantified using an error vector magnitude (EVM) measure. System level CDMA simulations are also used to evaluate the overall performance of this "RF space-time coding" technique. The results indicate a performance improvement equivalent to conventional space-time codes.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.018
GPT teacher head0.253
Teacher spread0.236 · 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 designSimulation or modeling
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

Citations5
Published2005
Admission routes1
Has abstractyes

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