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Record W2515924835 · doi:10.1109/mwsym.2016.7540386

Advanced envelope delta-sigma transmitter architecture with PLM power amplifier for multi-standard applications

2016· article· en· W2515924835 on OpenAlexaff
Maryam Jouzdani, Mohamed Helaoui, Fadhel M. Ghannouchi

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Power Amplifier Design
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsTransmitterAmplifierDelta-sigma modulationLinearityPredistortionElectronic engineeringBandwidth (computing)LinearizationBasebandRF power amplifierElectrical efficiencyRadio transmitter designElectrical engineeringEngineeringComputer sciencePower (physics)TelecommunicationsCMOSPhysics

Abstract

fetched live from OpenAlex

This paper presents a new modified envelope delta-sigma (DS) based transmitter architecture with good linearity and efficiency performance without applying any linearization techniques. For the proposed transmitter setup, a pulsed load modulation (PLM) amplifier is implemented and used for its high power efficiency at the back-off power levels. For high efficiency performance of the PA and maintaining the linearity of the system, an envelope DS modulator is utilized to quantized standard signals prior to the PA. Simulation results also show that higher coding efficiency of the quantized signal is achievable employing the envelope DS modulator instead of its Cartesian DS modulator counterpart. To validate the proposed technique, a transmitter prototype is implemented and tested with standard signals with various pick-to-average power ratios (PAPRs). Using this transmitter setup for a 3MHz bandwidth LTE signal with 7dB PAPR and a WiMAX signal with 1.25MHz bandwidth and 7.9dB PAPR, the average drain efficiency of about 45% and 44% are obtained, respectively, at the average output powers of 24.8dBm and 25.7dBm.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.931
Threshold uncertainty score0.844

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 head0.015
GPT teacher head0.244
Teacher spread0.229 · 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 designNot applicable
Domainnot available
GenreMethods

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".

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Citations1
Published2016
Admission routes1
Has abstractyes

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