Reconfigurable Doherty amplifier for efficient amplification of signals with variable PAPR
Bibliographic record
Abstract
This paper proposes a reconfigurable Doherty amplifier capable of efficiently amplifying signals with variable peak-to-average power ratios (PAPR). A small number of electronically tunable devices are used to preserve appropriate Doherty load modulation as the input signal PAPR varies. A reconfigurable Doherty amplifier demonstrator was designed and fabricated, using gallium nitride transistors, to operate at 2.6 GHz and to efficiently amplify signals with PAPR of 6, 9 and 12 dB. Continuous wave measurements revealed power added efficiencies of higher than 64% at 6 and 9 dB and 59% at 12 dB output back-off. A Volterra based digital predistortion technique was also applied to examine the linearizability of the demonstrator and an Adjacent Channel Power Ratio (ACPR) of better than 46 dBc was achieved using 20MHz excitation signals with different PAPR values.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".