Comparative Analysis of Sokal’s Equations versus Load-Pull Implementation of Class E Low-Pass Network
Bibliographic record
Abstract
In this paper, Class E power amplifiers (PA) aimed at frequency bandwidth of 3.4 GHz to 3.6 GHz (LTE 42) and 3.6 GHz to 3.8 GHz (LTE 43) respectively are designed with objective of attaining high efficiency. The viability of Sokal’s equations for present communication systems aimed at GHz are analyzed for high efficiency using HEMT (High-electron-mobility transistor) on Nitronex NPTB00004 as opposed to the Bipolar Junction Transistor used by Sokal in 1975. Load-pull configuration techniques aimed at the drain is implemented at the output matching network (OMN) and benchmarked against Sokal’s equation. At the OMN, to suppress harmonics, band-pass filters are employed for the LTE 42 and 43 respectively. Sokal’s equation shows that the drain must be conjugately matched before his equations are applied at the OMN. The efficiency at 3.4 GHz obtained for Sokal’s circuit is at 67 % and gain of 9.3 dB. More than 65% efficiency is obtained from load-pull network at 3.4 GHz to 3.76 GHz before filter implementation while showing gain above 7.8 dB. After filter addition at OMN, the efficiency is above 65% and gain above 8 dB for dual - band having bandwidth of 3.4389 GHz - 3.542GHz and 3.6569GHz - 3.8GHz.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".