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Record W1839865766 · doi:10.1109/lmwc.2015.2421317

Envelope Memory Polynomial Reformulation for Hardware Optimization of Analog-RF Predistortion

2015· article· en· W1839865766 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

VenueIEEE Microwave and Wireless Components Letters · 2015
Typearticle
Languageen
FieldEngineering
TopicAdvanced Power Amplifier Design
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsPredistortionEnvelope (radar)PolynomialRadio frequencyElectronic engineeringComputer scienceMathematicsAmplifierEngineeringTelecommunicationsCMOSMathematical analysis

Abstract

fetched live from OpenAlex

This letter addresses the very critical challenge facing the successful deployment of analog-RF predistortion (ARF-PD) and its hardware implementation complexity. A new envelope memory polynomial (EMP) expression is proposed to alleviate the dynamic range requirements for the analog multipliers and digital-to-analog converters. A two-step algorithm is devised to determine the coefficients of the proposed reformulated EMP within a specified hardware limitation. As proof-of-concept validation, a 20 W Doherty power amplifier driven by 20 MHz LTE signals was linearized using the conventional and newly proposed EMP expressions. An adjacent channel leakage ratio (ACLR) of -50.5 dBc was achieved with a dynamic range of about 50 dB for the proposed reformulated EMP and 155 dB for the conventional formulation.

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.462
Threshold uncertainty score0.693

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 head0.028
GPT teacher head0.224
Teacher spread0.197 · 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