Baseband predistortion techniques for M-QAM transmission using non-linear power amplifiers
Bibliographic record
Abstract
This paper presents a combined table look-up and polynomial-based predistortion (TLPPD) scheme for M-QAM transmission using non-linear power amplifiers. By applying a table look-up approach, the overall AM/AM and AM/PM distortion characteristics of the amplifier are divided into a small number of segments so that the non-linear behavior of each segment can be modeled by polynomials of lower order. As a result, the proposed scheme can offer both reduced complexity and faster convergence while maintaining the required accuracy as compared to the table look-up and polynomial-based techniques. Performance evaluation using simulation and experiments is presented. Power spectra and out-of-band emission of M-QAM systems using the proposed scheme and nonlinear power amplifier to achieve both high power and bandwidth efficiencies are also examined by simulation and experiments. Results indicate that the proposed scheme is suitable for applications of bandwidth-efficient M-QAM to PCS systems using non-linear amplifiers.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".