Wideband RF power amplifier predistortion using real-valued time-delay neural networks
Why this work is in the frame
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Bibliographic record
Abstract
this paper suggests the application of Real-Valued Time-Delay Neural Networks (RVTDNN) for Power Amplifier (PA) behavioral modeling and linearization. The Weights of the RVTDNN model and linearizer are identified using the Back Propagation Learning Algorithm (BPLA), which is applied to the measured input and output signals of the PA. The RVTDNN scheme is first successfully used to accurately predict the dynamic nonlinear behavior of a 250W LDMOS Doherty amplifier driven with 4 Carrier (4C) WCDMA signal. The RVTDNN is then applied for the construction of a digital predistortion to improve the linearity of the same Doherty amplifier. The ACPR of the linearized Doherty amplifier revealed an adjacent channel power ratio (ACPR) of better then 50dBc at the three offset frequency (5MHz, 10MHz, 15MHz).
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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