Identification and pre-compensation of the electrical memory effects in wireless transceivers
Why this work is in the frame
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Bibliographic record
Abstract
This paper proposes a novel approach to identify the electrical memory effects in wireless transceivers fed with a modulated signal. With this new proposed memory effect identification approach, the contribution of the electrical memory effects to the out-of-band emission can be distinguished easily. Furthermore, a Hammerstein and a memory polynomial pre-compensator are used to pre-correct the dynamic nonlinearity of the transceiver. Their corresponding pre-compensation performances are compared in terms of suppression level of the out-of-band emission caused by the electrical memory effects. A prototype of a wireless transceiver, which is based on an L-band 60-watt GaAs FET push-pull amplifier, is utilized to validate the proposed identification approach and evaluate the performances of the pre-compensators.
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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