Broadband and Linearity Enhanced Doherty Power Amplifier using Complex-valued Load Modulation
Bibliographic record
Abstract
This paper presents a novel output combining network to enable the extension of the bandwidth of the Doherty power amplifier (DP A) and improve its linearity. This combiner network brings about a complex-valued load modulation to take advantage of the continuous modes of operation for broadening the DP A bandwidth. It is also exploited to devise a nonlinear gain characteristic (AM/AM), which is complementary to the main transistor one and consequently improve the DP A linearity. Accordingly, a 50-W broadband DPA prototype with improved nonlinear gain characteristic is designed to operate over frequency band of 1.5-2.5 GHz while maintaining a drain efficiency in excess of 43 % and small gain variation around 1 dB over the entire 6dB Doherty region. Moreover, the linearizability of the designed DPA was verified under wideband (up to 80 MHz instantaneous bandwidth) and multi-band modulated stimuli using digital predistortion technique.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 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 teacher head, 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".