Homodyne Digitally Assisted and Spurious-Free Mixerless Direct Carrier Modulator With High Carrier Leakage Suppression
Bibliographic record
Abstract
In this paper, a new method to design a digitally assisted and spurious-free direct carrier mixerless modulator based on the six-port correlator is proposed. The calibration of the modulator based on modified Cartesian memory polynomial (MCMP) is used to linearize and mitigate hardware impairment of the whole system. The modulation and the up conversion are performed by using the variable loads controlled by the differential in-phase and quadrature-phase baseband voltages together with common-mode voltages. The proposed MCMP is able to compensate for nonlinearity, frequency responses, residual carrier leakage, crosstalk between the in-phase and the quadrature-phase data. The proof-of-concept of digitally assisted mixerless modulator is developed and its performance is assessed at 2.6 GHz with modern communication signals. The error vector magnitudes between the input ideal baseband signals and the up-converted radio frequency signals are all between 2% and 4%. The residual carrier leakage, which remains present after imperfect suppression through hardware means, degrades the overall system performance and it can be suppressed completely by means of the proposed memory polynomial model.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".