A 28-GHz Beamforming Doherty Power Amplifier With Enhanced AM-PM Characteristic
Bibliographic record
Abstract
This article presents a beamforming Doherty power amplifier (B-DPA) for the 28-GHz fifth-generation (5G) newradio band. The proposed B-DPA is based on a new combiner topology that allows the current profile in the auxiliary branch of the DPA to be relaxed while simultaneously canceling the amplitude-to-phase (AM-PM) distortion exhibited in the active devices. This approach enables efficiency and linearity enhancements. In addition, the DPA is augmented with high-accuracy digitally assisted vector multipliers at its input stage to provide the required relative and absolute phase adjustments for proper Doherty operation and the overall phase shift required for beamforming. A proof-of-concept prototype was implemented in the 45-nm silicon on insulator (SOI)-CMOS technology. Measurement results reveal that the proposed B-DPA demonstrated good Doherty operation with drain efficiencies of 18%-20% and 33%-35% at 6-dB back-off and saturation power (Psat, 18 dBm) levels, respectively, between 28 and 30 GHz. In particular, excellent AM-PM characteristics were noted with a peak value of only 1.5° up to Psat, which remained below 2.5° as the B-DPA was swept with a 0° to 360° phase shift. Finally, modulated-signal tests revealed error vector magnitudes of 3.1% and 0.9% for 4-MHz × 100-MHz orthogonal frequency division multiplexing (OFDM) signals before and after applying digital predistortion, respectively.
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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) | 0.002 | 0.001 |
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.
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".