An Enhanced Binary Particle Swarm Optimization for Pruning Digital Predistortion Models
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Bibliographic record
Abstract
In this letter, we propose an enhanced binary particle swarm optimization (PSO) algorithm with symmetrical uncertainty (EBPSO-SU) to reduce the complexity of the digital predistortion (DPD) model. In millimeter-wave (mm-wave) communication systems, the power consumption issue is notable due to the considerable number of redundant terms in the DPD models. To prune these terms, the correlation between the label (output signal) and features (basic function terms) is first leveraged for swarm initialization. Subsequently, the EBPSO algorithm, incorporating a modified velocity-to-position mapping formula, is employed to identify key terms of the model. Measurement results from a 28 GHz power amplifier operating with a 200 MHz input signal illustrate that the proposed pruning algorithm can reduce the complexity of the full generalized memory polynomial (GMP) model by 90% while ensuring equivalent performance.
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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 | 0.001 |
| 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 it