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Record W2610951593 · doi:10.1049/iet-com.2016.1432

Cartesian augmented Hammerstein model for non‐linearity and I/Q impairments compensation in concurrent dual‐band transmitters

2017· article· en· W2610951593 on OpenAlex
Souhir Lajnef, Noureddine Boulejfen, Fadhel M. Ghannouchi

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

VenueIET Communications · 2017
Typearticle
Languageen
FieldEngineering
TopicAdvanced Power Amplifier Design
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsComputer scienceAmplifierLinearityControl theory (sociology)TransmitterInfinite impulse responseElectronic engineeringDigital filterBandwidth (computing)TelecommunicationsArtificial intelligenceEngineering

Abstract

fetched live from OpenAlex

In this study, a novel model for the joint compensation of dual‐band power amplifier (PA) distortion and in‐phase/quadrature (I/Q) imbalance, which are the dominant impairments of wireless signal transmitters, in a complexity reduced structure is proposed. This model is mainly based on the augmented Hammerstein approach in a Cartesian form so that a static block is intended to model the PA non‐linearity and the modulator I/Q imbalance while a finite impulse response filter based block is used to model the PA memory effects. The proposed approach reduces significantly the complexity of the proposed model compared with the recently published memory polynomial models. Experiments with and without I/Q modulator impairments have been carried out on a dual‐band PA to verify the accuracy and the performance of the linearisation technique based on the proposed model. The experimental results have revealed a good impairments reduction with much less model coefficients compared with the recently published ones.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.843
Threshold uncertainty score0.602

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 head0.058
GPT teacher head0.320
Teacher spread0.261 · 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