Analytical prediction of spectral regrowth and correlated and uncorrelated distortion in multicarrier wireless transmitters exhibiting memory effects
Bibliographic record
Abstract
Measurement of non-linearity effects in wireless transmitters had been always difficult under complex digitally modulated signals. On the other hand, blind time domain simulation of these effects is generally time consuming and insufficient. In this study, the authors present new frequency domain closed-form formulas for predicting the spectral regrowth in wireless communication systems/subsystems with fifth-order non-linearity exhibiting memory effects. Particularly, the suggested formulas estimate the power spectral density, as well as the undesirable adjacent-channel and co-channel emissions of the modelled device, under phase-aligned and randomly phase-modulated multitone excitations. In addition, they are able to predict the correlated and uncorrelated distortion powers separately. The efficiency and robustness of the proposed approach has been demonstrated by predicting the output of a laterally diffused metal oxide semiconductor Doherty-based power amplifier. The obtained results have been compared to measurements and those of time-domain simulators and have revealed good accuracy and time efficiency.
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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 | 0.002 |
| 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 | 0.001 |
| 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 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".