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Record W2124880482 · doi:10.1049/iet-map.2012.0663

Distortion and impairments mitigation and compensation of single‐ and multi‐band wireless transmitters (invited)

2013· article· en· W2124880482 on OpenAlexaff
Fadhel M. Ghannouchi, Mayada Younes, Meenakshi Rawat

Bibliographic record

VenueIET Microwaves Antennas & Propagation · 2013
Typearticle
Languageen
FieldEngineering
TopicAdvanced Power Amplifier Design
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsCompensation (psychology)WirelessDistortion (music)Electronic engineeringTransmitterTelecommunicationsComputer scienceElectrical engineeringEngineeringBandwidth (computing)PsychologyChannel (broadcasting)Amplifier

Abstract

fetched live from OpenAlex

Transmitter digital domain linearisation solutions are constantly evolving to extract optimum benefits in terms of cost, performance and flexibility. This study highlights the current and futuristic trends in the arena of transmitter system modelling and digital domain compensation for radio frequency distortions of non‐linear power amplifiers and wireless transmitters in case of single‐band wireless transmitter, which is further extended to a dual‐band transmitter. Indeed, the dual‐band transmitter results in severe non‐linear distortion as compared to the single‐band transmitter when operated in concurrent mode, due to the additional inter‐modulation products generated by the dual‐band transmitted signals. Hence, in addition to the intermodulation products and memory effects exhibited in a single‐band transmitter, the cross‐modulation effects of the dual‐band signals should be compensated for as well in a dual‐band transmitter. The effects of the modulator imperfections such as gain and phase imbalances, phase errors and DC offsets and their impact on the feedback loop of a digital predistortion system are also analysed. A thorough comparison between the state‐of‐the‐art behavioural models and their application to digital predistortion technique of power amplifier is presented in terms of performance and complexity. Model performance assessment is discussed through simulation and experimental results for both single‐ and dual‐band systems.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.312
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 communication0.0000.001
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 head0.195
Teacher spread0.186 · 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 designBench or experimental
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

Citations29
Published2013
Admission routes1
Has abstractyes

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