A Reflection-Aware Unified Modeling and Linearization Approach for Power Amplifier Under Mismatch and Mutual Coupling
Bibliographic record
Abstract
The behavior of a power amplifier (PA) is substantially affected by the output mismatch and mutual coupling in modern compact transmitters. To date, different works in the literature address the problem of coupling and mismatch separately, which are limited in terms of performance with a higher level of mismatch and mutual coupling. This paper identifies the reflection at the PA-antenna interface to be an effective parameter to unify the problem of mismatch and mutual coupling. Thus, a reflection-aware PA modeling and linearization method is proposed to compensate the adverse effect of mismatch and/or mutual coupling. The performance of the proposed method is investigated with a class AB and a Doherty PA under wide range of output mismatch and/or mutual coupling conditions with a 20-MHz WCDMA signal. The proposed method shows robust performance with an average adjacent channel power ratio better than 45 dBc. Such robust linearization performance under diverse output mismatch and mutual coupling conditions is highly desirable for modern and future communication systems that are subject to undergo rapid fluctuations under antenna matching and cross-coupling conditions.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".