Adaptive polynomial predistorters for M‐QAM transmission using non‐linear power amplifiers
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract In this paper, adaptive baseband polynomial predistortion techniques are introduced to counter‐balance the AM/AM and AM/PM non‐linear effects of the transmit power amplifier. The proposed polynomial predistortion scheme is based on polar coordinate representation. Both LMS and RLS concepts are used to derive the adaptive algorithms. An enhanced LMS‐based algorithm with fast convergence and low complexity is proposed. For very fast convergence, a cascaded RLS‐based adaptive polynomial predistorter structure is introduced. The performance of the proposed schemes in terms of intermodulation distortion, spectral regrowth, and convergence rate are examined. The obtained results show that the polynomial predistortion schemes can be used in M‐QAM transmitters with power amplifiers operating near saturation to achieve a highest power efficiency. Copyright © 2006 John Wiley & Sons, Ltd.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 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 it