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Record W2069149356 · doi:10.1109/rws.2012.6175382

Frequency agile RF filter for interference attenuation

2012· article· en· W2069149356 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Adaptive Filtering Techniques
Canadian institutionsEricsson (Canada)Carleton University
Fundersnot available
KeywordsAttenuationElectronic engineeringRadio frequencyFilter (signal processing)Transfer functionComputer scienceInterference (communication)Low-pass filterEngineeringElectrical engineeringTelecommunicationsPhysicsOpticsChannel (broadcasting)

Abstract

fetched live from OpenAlex

This paper introduces a frequency agile RF filter for interference attenuation in a base station RF frontend. Digital and RF systems are combined in a feed-forward architecture. This architecture provides a frequency response with multiple tunable transfer function zeros. This feed-forward architecture is called the hybrid RF-DSP feed-forward filter. Measurements demonstrate successful interferer suppression for operation at several bands between 800 and 1800 MHz. The group delay mismatch between the feed-forward paths is reduced with a delay line to achieve between 32 to 24 dB of attenuation for interferers with bandwidths from 1 to 8 MHz. The digital filter used within the prototype had 32 complex taps, thereby providing the RF filter with 32 tunable transfer function zeros.

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.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.813
Threshold uncertainty score0.338

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 head0.036
GPT teacher head0.270
Teacher spread0.234 · 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

Quick stats

Citations9
Published2012
Admission routes1
Has abstractyes

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