Phase calibration for coherent multi-harmonic modulated signal measurements using nonlinear vector network analyzer
Bibliographic record
Abstract
This paper proposes a novel phase calibration approach to enable multi-harmonic modulated signal measurements using existing nonlinear network analyzer (NVNA) receivers configured in wideband mode. The envelopes around the harmonics are captured sequentially so that the dynamic range (DR) of the measurement system is not compromised. A reference signal generated by a comb generator is used to ensure phase coherency between the harmonics, precluding the need to use a small frequency grid that typical solutions require. To validate its ability to make accurate measurements of multi-harmonic modulated signals, the proposed NVNA-based method is tested against a state-of-the-art oscilloscope. The proposed approach is applied first to an 8-tone signal that covers 14 MHz, then on a 5 MHz 1C-WCDMA signal. Both signals have three harmonics with the fundamental frequency at 1 GHz. The phase accuracy of the measured signal is within ±1.5° and ±10° for the first and second test signals, respectively.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".