Augmented Dual-Band Digital Predistorter for Reducing Cross-Band Intermodulation Distortion Using Predictive Injection Technique
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Bibliographic record
Abstract
In this paper, an augmented dual-band digital predistortion (DPD) technique for reducing the cross-band intermodulation distortion (IMD) using predictive injection technique is proposed to address some of the shortcomings of dual-band DPDs. The technique alleviates the need to observe the cross-band third-order IMD (IMD3) terms in the feedback loop by predicting the distortion terms and generating synthetic signals, which are then injected at the transmitter side. To highlight the issue, the wideband and dual-band DPD architectures and their respective limitations are briefly outlined. The theory behind the proposed concept is developed, and practical measurements performed using a Class AB power amplifier driven by a long-term evolution signal are provided to support the theory. The results obtained show that the proposed method achieves promising performance in mitigating the cross-band IMD3 issue faced by dual-band DPDs. This technique can be extended to mitigate higher order cross-band distortion as well.
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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