An Accurate Predistorter Based on a Feedforward Hammerstein Structure
Bibliographic record
Abstract
This paper presents a feedforward Hammerstein structure that is proposed for the modeling and digital predistortion of the dynamic nonlinear behavior of the wideband radio frequency power amplifiers and wireless transmitters. This model consists of two loops, one used as a signal cancellation loop and the second used as distortion injection loop. The main signal cancellation loop is responsible for the characterizing of the PA dynamics through a Hammerstein model. Indeed, the distortion injection loop was found to complement the main signal cancellation loop by adding an accurate means of modeling the nonlinear dynamics of the intermodulation distorted signal for the better mimicking of the intermodulation distortion products especially in the out-of-band regions. Its accuracy is assessed in behavioral modeling and digital predistortion, by comparing it to other state-of-the-art models. The measurement results show an adjacent channel power ratio of almost$-$50 dBc and a normalized mean square error of less than$-$42 dB.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".