A Mixed-Technology Asymmetrically Biased Extended and Reconfigurable Doherty Amplifier With Improved Power Utilization Factor
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In this paper, we present a mixed-technology extended Doherty amplifier using asymmetrical voltage biasing with an LDMOS main device and a GaN auxiliary device to improve the power utilization factor of the amplifier. Moreover, in contrast to previous work, the amplifier can achieve reconfigurable back-off power ranges and an extended bandwidth without using a mixed-signal setup. The analysis also highlights the relationship between power utilization and the range of the reconfigurable back-off power level. Finally, we demonstrate that the proposed amplifier can be optimally configured for a given modulated signal to obtain the highest average efficiency. A 180-W mixed-technology prototype Doherty amplifier measured peak and back-off efficiencies greater than 50% when configured for 6, 8, and 10 dB of back-off power level at 790, 870, and 960 MHz under continuous-wave stimulus. The amplifier is highly linearizable when driven with 20-MHz long-term evolution and WCDMA signals, achieving adjacent channel power ratio of better than -50 dBc after digital pre-distortion linearization.
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.
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) | 0.000 | 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 it