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Record W2115605830 · doi:10.1109/cnsr.2007.16

Antenna Load Mismatch Effects in EER-Based Transmitters for Digital Audio Broadcasting

2007· article· en· W2115605830 on OpenAlexaff
Scott H. Melvin, Manmeet S. Goldy, Jacek Ilow

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Power Amplifier Design
Canadian institutionsDalhousie University
Fundersnot available
KeywordsElectronic engineeringComputer scienceAntenna (radio)Electrical engineeringAntenna tunerAntenna noise temperatureTelecommunicationsAntenna measurementEngineeringAntenna factor

Abstract

fetched live from OpenAlex

As terrestrial audio broadcasting is moving from the analog to the digital era, there is an interest from the broadcasting industry to re-examine the existing amplitude modulation (AM) and frequency modulation (FM) hardware. The objective is to identify potential problems which may arise when using digital signals with the existing systems. In particular, this paper analyzes the effects that an antenna impedance mismatch has on the spectrum regrowth of a hybrid analog-digital AM signal at the passband. The interest in this research stems from the difficulty in controlling the antenna impedance as it may vary with weather conditions e.g., icing on the antenna. Spectrum regrowth results are first presented in this paper when modelling the antenna load as a resonant circuit for both series and shunt load topologies when the inverse Chebychev reconstruction filter is deployed in the envelope elimination and restoration (EER) amplifier. Different selectivity factors, Q, for antenna resonant circuit are considered. Following this, attempts to design more robust filters are offered that would be of the same order and would provide improved spectral performance when working with the antenna impedance deviations from the nominal resistive value of 50 Omega.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.897
Threshold uncertainty score0.853

Codex and Gemma teacher scores by category

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.009
GPT teacher head0.226
Teacher spread0.217 · 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 teacher head, 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

Citations2
Published2007
Admission routes1
Has abstractyes

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