Bandwidth Performance Analysis of DLM PAs Including the Class-A/B/J Continuum
Bibliographic record
Abstract
In this paper, a new method is presented to analyze the bandwidth performance of power amplifiers (PAs) including the Class-A/B/J Continuum for dynamic load modulation (DLM). Due to the introduced biasing operation factor p, the analysis of bandwidth performance of DLM Class-J PAs can be extended to other modes, such as deep Class-AB mode. With the help of MATLAB software, the relationship between the drain efficiency (η) and output power back-off (OPBO) at the current generator plane (CGP) is demonstrated clearly. At the CGP, the proposed method indicates that when p = 0, the fractional bandwidth (FBW) of DLM PAs is improved from 73% to 141% compared with the results at the extrinsic plane (EP). When p is increased to 0.2, the FBW of DLM PAs can be improved from 141% to 156%. Furthermore, the proposed method in this work provides clear guideline to do a general analysis on the bandwidth performance of DLM PAs including the Class-A/B/J Continuum, and it also provides potential theoretical guidance for engineers to design wideband DLM PAs.
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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 | 0.001 |
| 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 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".