Design of high‐efficiency and broadband‐tuned class AB power amplifier
Bibliographic record
Abstract
Abstract The design of broadband matching networks (MNs) exploiting filter theory is presented in this article for synthesizing broadband and highly efficient power amplifiers (PAs).Starting from sets of optimum impedances over the design frequency (obtained from load/pull measurement), the MNs are designed using a systematic approach. The impact of the second harmonic termination on the transistor performance is investigated and used to optimize the power efficiency over broad frequency range. Two PAs were designed with the proposed methodology using 25‐W GaN device. The designs targeted the frequency bands of 1.8–2.2 GHz (20% BW) and 1.8–2.7 GHz (40% BW). The former achieved the drain efficiency (DE) of about 70% and output power of 45.5 dBm (±1 dB), whereas the latter delivered a DE of about 60% and output power of 45.5 dBm. © 2010 Wiley Periodicals, Inc. Microwave Opt Technol Lett 53:395–398, 2011; View this article online at wileyonlinelibrary.com. DOI 10.1002/mop.25710
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.
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 | 0.001 |
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".