Generalised two‐box cascaded Hammerstein‐like digital predistorter for wide‐band RF power amplifiers
Bibliographic record
Abstract
A generalised two‐box cascaded Hammerstein‐like (GTBC‐H) digital predistorter is proposed for linearising wide‐band RF power amplifiers (PAs). The GTBC‐H predistorter is composed of a static nonlinearity block for countervailing the strong static nonlinearities and a dynamic nonlinearity block for compensating the memory effects of RF PAs. The proposed predistorter adds extended cross‐terms of the leading terms and some lagging envelope terms in the dynamic nonlinearity block to compensate the memory effects of wide‐band RF PAs more effectively. A 460 MHz and a 1.94 GHz Doherty RF PA are utilised to validate the performance of the proposed predistorter when a three‐carrier wide‐band CDMA and a single‐carrier long‐term evaluation signal are applied separately. The validation results illustrate that the proposed GTBC‐H predistorter can further suppress the residual out‐of‐band emission over the augmented Hammerstein, the enhanced Hammerstein and the parallel‐LUT‐MP‐EMP predistorter.
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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 | 0.000 |
| 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 | 0.001 | 0.001 |
| 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".