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Record W1972828360 · doi:10.2514/6.2010-3463

Highly Efficient DSP-Guided Power Amplifier (PA) for Wireless OFDM Applications

2010· article· en· W1972828360 on OpenAlexaff
Mudassar Nisar, Antonio Ginart, Irtaza Barlas, Patrick W. Kalgren, Michael Roemer

Bibliographic record

VenueAIAA Infotech@Aerospace 2010 · 2010
Typearticle
Languageen
FieldEngineering
TopicPAPR reduction in OFDM
Canadian institutionsImpact
Fundersnot available
KeywordsOrthogonal frequency-division multiplexingWirelessComputer scienceAmplifierDigital signal processingElectronic engineeringElectrical engineeringTelecommunicationsBandwidth (computing)EngineeringComputer hardwareChannel (broadcasting)

Abstract

fetched live from OpenAlex

In this work, a high efficiency double-enveloping DSP-guided hybrid power amplifier design is presented for wide band applications. The high peak-to-average power ratio (PAPR) of OFDM signals is a major bottleneck in the implementation of wide-band high efficiency transmitters. In the proposed design, low-complexity digital signal processing (DSP) techniques are used for PAPR minimization and estimation of peak-value average of the incoming signal; the average peak-value of the signal is used to select the rail voltage of the hybrid amplifier. The incorporation of the DSP techniques for double enveloping and PAPR reduction of the incoming signal increases the efficiency of the hybrid amplifier to more than 80%.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.656
Threshold uncertainty score1.000

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 science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.010
GPT teacher head0.240
Teacher spread0.230 · 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.

Study designNot applicable
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

Citations0
Published2010
Admission routes1
Has abstractyes

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