A Highly Linear GaN MMIC Doherty Power Amplifier Based on Phase Mismatch Induced AM–PM Compensation
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Bibliographic record
Abstract
This article presents a highly linear Doherty power amplifier (DPA) based on phase mismatch. When output phase mismatch (OPM) is introduced, i.e., the phase shift of the output impedance transformer deviates from 90°, the power-combining network (PCN) will exhibit a certain amplitude-to-phase (AM–PM) characteristic. When input phase mismatch (IPM) is introduced, i.e., the main and auxiliary branches are not phase-aligned, the AM–PM of the PCN can be further finely tuned. By choosing proper OPM and IPM, the AM–PM of the overall DPA can be compensated by that of the PCN while maintaining reasonable back-off and saturated performances. Moreover, the PCN with phase mismatch shows gain expansion, and thus the amplitude-to-amplitude (AM–AM) distortion of the DPA can also be improved to some extent. A fully integrated DPA is implemented in a <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$0.25~\mu \text{m}$ </tex-math></inline-formula> gallium nitride (GaN)-HEMT process to validate the proposed method. The fabricated DPA realizes an AM–PM of 2° and an AM–AM of 0.3 dB at 6.3 GHz, with a saturated power of 41.1 dBm and a 6 dB back-off drain efficiency (DE) of 45%. Applying a 200 MHz signal with a 7.8 dB peak-to-average power ratio (PAPR), a raw adjacent channel power ratio (ACPR) of −42 dBc and an average DE of 37.4% are measured at the output power of 33.1 dBm. When the carrier frequency is swept from 6.1 to 6.5 GHz, a raw ACPR below −39 dBc and an average DE better than 37% are maintained.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
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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 it